Control device for vehicle

Abstract

To prevent a vehicle from being unable to travel.SOLUTION: In a vehicle (1) capable of switching from automated driving to manual driving, a battery charging rate is estimated that changes with time due to power consumption when the automatic driving of the vehicle (1) is performed, and an actual charging rate of a battery (11) is acquired when the vehicle performs the automatic driving. During the automatic driving, when an actual charging rate of the battery (11) becomes lower than an estimated charging rate of the battery by a predetermined value or more, the automated driving is switched to the manual driving.SELECTED DRAWING: Figure 10

Description

[Technical Field]

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

[0002] There is known an information processing device that predicts the planned driving distance of each electric vehicle based on the expected demand for dispatching a plurality of electric vehicles, acquires information about the remaining battery charge and battery degradation state of each electric vehicle, determines whether each electric vehicle needs to be charged based on the predicted value of the planned driving distance of each electric vehicle, the remaining battery charge and battery degradation state of each electric vehicle, and determines a charging schedule and a dispatch schedule for each electric vehicle based on the determination of whether each electric vehicle needs to be charged (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-96496 Summary of the Invention [Problem to be solved by the invention]

[0004] However, if the charging schedule and dispatch schedule for each electric vehicle are determined in this manner, there is a risk that the actual remaining battery charge will diverge from the predicted remaining battery charge, causing the electric vehicle to run out of power and become unable to run. [Means for solving the problem]

[0005] According to the present invention, in a vehicle that can be switched from automatic driving to manual driving, the vehicle is equipped with a battery and a processor, and the processor Estimate the battery charge rate that changes over time due to power consumption when the vehicle is being driven autonomously, Obtain the actual battery charge rate when autonomous driving is in progress, A vehicle control device is provided that switches from autonomous driving to manual driving when the actual battery charging rate drops below the estimated battery charging rate by a predetermined value or more during autonomous driving. [Effects of the Invention]

[0006] This can prevent the vehicle from becoming unable to travel. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a diagram showing the functional configuration of a vehicle. [Figure 2] FIG. 2 is a diagram showing the entire control system of the vehicle. [Figure 3] FIG. 3 is a diagram showing the configuration of the electronic control device. [Figure 4] FIG. 4 is a diagram illustrating the functional configuration of a vehicle control system. [Figure 5] FIG. 5 is a diagram showing an example of a charging schedule. [Figure 6] 6A, 6B, and 6C are graphs showing the change in SOC over time. [Figure 7] 7A, 7B, 7C, and 7D are diagrams for explaining correction coefficients and the like. [Figure 8] FIG. 8 is a flowchart for carrying out a charging plan. [Figure 9] FIG. 9 is a flowchart for calculating the actual SOC. [Figure 10] FIG. 10 is a flowchart for executing a vehicle operation switching procedure. DETAILED DESCRIPTION OF THE INVENTION

[0008] FIG. 1 shows the functional configuration of a vehicle 1 whose driving is controlled by an automatic driving system. This vehicle 1 can also be driven manually. The present invention will be described below using the example in which vehicle 1 is a manually-driven automatic driving bus. Referring to FIG. 1, reference numeral 10 denotes a vehicle drive unit for applying driving force to the drive wheels of vehicle 1; 11 denotes a battery; 12 denotes a braking device for braking vehicle 1; 13 denotes a steering device for steering vehicle 1; 14 denotes the doors of vehicle 1, i.e., a door opening / closing device for opening and closing the doors of the automatic driving bus; 15 denotes an air conditioner for heating and cooling the interior of the vehicle; 16 denotes a communication device; and 17 denotes an electronic control unit mounted in vehicle 1. As shown in FIG. 1, electronic control unit 17 is a digital computer and includes a CPU (microprocessor) 19, a memory 20 consisting of ROM and RAM, and an input / output port 21, all connected to each other by a bidirectional bus 18.

[0009] 1, the vehicle drive unit 10 is composed of an electric motor driven by a battery 11, and the drive wheels are drive-controlled by the electric motor in accordance with an output signal from an electronic control unit 17. Braking control of the vehicle 1 is performed by a braking device 12 in accordance with an output signal from the electronic control unit 17, and steering control of the vehicle 1 is performed by a steering device 13 in accordance with an output signal from the electronic control unit 17. Note that the electronic control unit 17 can be composed of a single electronic control unit or multiple electronic control units.

[0010] Meanwhile, as shown in FIG. 1, the vehicle 1 is equipped with a detection device 22 consisting of various sensors. For example, sensors necessary for the vehicle 1 to perform autonomous driving, i.e., sensors that detect the state of the vehicle 1 and surroundings detection sensors that detect the surroundings of the vehicle 1, are installed. In this case, acceleration sensors, speed sensors, and azimuth sensors are used as sensors that detect the state of the vehicle 1, and surroundings detection sensors that detect the surroundings of the vehicle 1 include on-board cameras that capture images of the front, sides, and rear of the vehicle 1, lidars, radars, etc. In addition, the vehicle 1 is equipped with a sensor, for example, a camera, that can detect people getting on and off the vehicle 1, i.e., passengers getting on and off the autonomous bus, and the number of passengers in the vehicle 1 is detected from image data from this camera. Furthermore, the vehicle 1 is equipped with a sensor for detecting the outside air temperature.

[0011] The vehicle 1 is further provided with a GNSS (Global Navigation Satellite System) receiver 23, a map data storage device 24, a navigation device 25, and a notification device 26 that notifies necessary information via a display screen or voice. The GNSS receiver 23 can detect the current position (e.g., latitude and longitude) of the vehicle 1 based on information obtained from multiple artificial satellites. Therefore, the current position of the vehicle 1 can be obtained by the GNSS receiver 23. For example, a GPS receiver is used as the GNSS receiver 23. Meanwhile, the map data storage device 24 stores map data and the like necessary for the vehicle 1 to perform autonomous driving. The detection device 22, the GNSS receiver 23, the map data storage device 24, the navigation device 25, and the notification device 26 are connected to the electronic control unit 17.

[0012] Figure 2 shows an overall diagram of a vehicle control system suitable for implementing this invention. Referring to Figure 2, 2 indicates a communication network, 3 indicates an operation management server managed by a bus operation service provider or the like, 4 indicates a regional information management server that collects and manages various regional information, and 5 indicates a vehicle 1, i.e., a garage for an autonomous bus, with charging equipment 6 installed in garage 5 to charge battery 11 of vehicle 1.

[0013] 3 shows an electronic control device 30 installed in the fleet management server 3. Referring to FIG. 3, the electronic control device 30 is composed of an electronic control unit 31 and a notification device 32. The electronic control unit 31 is made up of a digital computer and includes a CPU (microprocessor) 34, memory 35 consisting of ROM and RAM, and input / output ports 36, which are connected to each other by a bidirectional bus 33. Electronic control devices having a configuration similar to that of the electronic control device 30 are installed in the regional information management server 4 and the charging equipment 6, and the vehicle 1, fleet management server 3, regional information management server 4, and charging equipment 6 can communicate with each other via the communication network 2.

[0014] Fig. 4 shows the functional configuration of the vehicle 1, the fleet management server 3, and the regional information management server 4 shown in Fig. 2. Referring to Fig. 4, the vehicle 1 is equipped with an automatic driving control unit 40 for performing automatic driving control, a passenger authentication unit 41 that can acquire information on the number of passengers and the like, and a charging planning unit 42 for determining a charging schedule for the battery 11 mounted in the vehicle 1. The charging rate of the battery 11 is called SOC (State of charge), and when the battery 11 is fully charged, the charging rate, i.e., the SOC, is 100%, and when the battery 11 is zero, the charging rate, i.e., the SOC, is 0%. As shown in FIG. 4, the vehicle 1 further includes an SOC estimation value calculation unit 43 for calculating the charging rate of the battery 11, i.e., an estimated value of the SOC, an actual SOC calculation unit 44 for calculating the actual charging rate (actual charging rate) of the battery 11, i.e., the actual SOC, and a manual driving switching unit 45 for switching from automatic driving to manual driving based on the estimated value of the SOC and the actual SOC.

[0015] Meanwhile, as shown in Fig. 4, the traffic management server 3 includes an operation planning unit 50 that can create both a fixed-time, fixed-route operation plan for the vehicle 1 and an on-demand operation plan for the vehicle 1. Furthermore, the traffic management server 3 includes a reservation unit 51 that accepts reservations when the operation mode of the vehicle 1 is on-demand. When a reservation is accepted by the reservation unit 51, an operation plan according to the reservation details is created by the operation planning unit 50. Furthermore, as shown in Fig. 4, the area information management server 4 includes an area information unit 52 that acquires event information in the area where the vehicle 1 travels and information on the degree of congestion in the area where the vehicle 1 travels.

[0016] Next, an example of a method for determining charging timing will be described, taking as an example a case where a fixed-time, fixed-route operation plan for that day is created before the autonomously driven vehicle 1 begins operating. When the autonomously driven vehicle 1 begins operating, the battery charging rate, i.e., the SOC, gradually decreases over time due to power consumption. In an embodiment of the present invention, the battery charging rate, i.e., the SOC, is estimated at each hour after the autonomously driven vehicle 1 begins operating, and charging timing is determined so that the battery 11 of the vehicle 1 can be charged by the charging device 6 before the estimated battery charging rate, i.e., the estimated SOC, falls below an allowable lower limit SOCX. This lower limit SOCX is set to a value that allows the vehicle 1 to travel to the garage 5 even if the vehicle 1 is located on a route farthest from the garage 5.

[0017] FIG. 5 shows an example of determining appropriate charging timing based on an estimated SOC. FIG. 5 illustrates a case in which three vehicles 1 (vehicle A, vehicle B, and vehicle C), i.e., three autonomous buses, are operating on a fixed schedule and route, with one round trip taking one hour, charging time required being 1.5 hours, and a maximum of two trips that can be operated simultaneously. In FIG. 5, "trip 1," "trip 2," ..., "trip N" represent the first, second, ..., Nth trips, respectively. "Charge" indicates the charging period, and the period indicated by "-" indicates the waiting period in the garage 5. As described above, the operation plan and charging timing shown in FIG. 5 are determined based on an estimated SOC. Therefore, it is necessary to first calculate an estimated SOC. Next, an example of a method for calculating an estimated SOC will be described.

[0018] In an embodiment according to the present invention, the battery 11 mounted on the vehicle 1 is charged by the charging equipment 6 installed in the garage 5 before the vehicle 1 departs from the garage 5, and therefore charging of the battery 11 is completed before the vehicle 1 departs from the garage 5. In this case, if the battery charging rate at the time of completion of charging is represented as SOCA, the estimated value of the SOC when time t has elapsed since the vehicle 1 departed from the garage 5 (hereinafter simply referred to as "after t hours have elapsed") is calculated by subtracting the amount of SOC decrease ΔSOC after t hours have elapsed from the battery charging rate SOCA at the time of completion of charging. Therefore, first, an example of a method for calculating the amount of SOC decrease ΔSOC after t hours have elapsed will be described.

[0019] The energy EX consumed from when the vehicle 1 leaves the garage 5 until time t has elapsed is the sum of the loss Ef due to friction from when the vehicle 1 leaves the garage 5 until time t has elapsed, the change in potential energy ΔEh, and the change in kinetic energy ΔEv, as shown in the following equation. EX=Ef+ΔEh+ΔEv The loss due to friction Ef is the integral value of the loss f due to instantaneous friction from the time when the vehicle 1 leaves the garage 5 until the time t has elapsed. Here, if v is the vehicle speed, the loss f due to instantaneous friction is expressed as a quadratic equation of the vehicle speed v as follows: f=av 2 +bv+c (a, b, c are constants) On the other hand, the amount of change in potential energy ΔEh is expressed by the following equation using the altitude difference Δh between the garage 5 and the position after t time has elapsed. ΔEh = mgΔh (m is the mass of vehicle 1, g is the acceleration due to gravity) In addition, the change amount of kinetic energy ΔEv is expressed by the following equation, where v0 is the vehicle speed when departing from the garage 5 and v is the vehicle speed at the position after t time has elapsed. ΔEh=1 / 2 m(v 2 -v0 2 )

[0020] On the other hand, if the conversion efficiency when the output of the battery 11 is converted into mechanical output is approximated by a constant μ, the energy ΔEb taken out from the battery 11 until the time t has elapsed after the vehicle 1 leaves the garage 5 is expressed by the following equation: ΔEb=EX / μ On the other hand, if the charge capacity of the battery 11 is Q and the output voltage of the battery 3 is approximated by a constant V, the energy Eq possessed by the battery 11 is expressed by the following equation. Eq=QV Therefore, the SOC decrease amount ΔSOC after the lapse of time t is expressed by the following equation. ΔSOC=ΔEb / Eq In this way, the SOC decrease amount ΔSOC after the elapse of each elapsed time t, i.e., the SOC decrease amount ΔSOC at each elapsed time t, is calculated. In calculating the SOC decrease amount ΔSOC at each elapsed time t, the altitude difference Δh is calculated based on the map data stored in the map data storage device 24, and the vehicle speed v is set to a preset traveling speed.

[0021] Strictly speaking, the conversion efficiency constant μ depends on the drive power and vehicle speed v of the vehicle 1, so ΔEb is a function of the drive power and vehicle speed v of the vehicle 1, and the output voltage V of the battery 11 depends on the battery charging rate SOC, so Eq is a function of SOC. Therefore, when precisely calculating the SOC decrease amount ΔSOC at each elapsed time t, ΔSOC is calculated taking into account changes in the drive power, vehicle speed v, and SOC of the vehicle 1. Note that a description of the calculation method for ΔSOC when precisely calculating the SOC decrease amount ΔSOC at each elapsed time t will be omitted here.

[0022] Once the SOC drop amount ΔSOC at each elapsed time t is calculated in this manner, an estimated SOC value at each elapsed time t is calculated by subtracting the calculated SOC drop amount ΔSOC at each elapsed time t from the battery charging rate SOCA at the time of charging completion. However, this SOC drop amount ΔSOC at each elapsed time t is affected by the number of passengers in the vehicle 1 and repeated deceleration and stopping due to traffic congestion, and is particularly affected by the power consumption of the air conditioner installed in the vehicle 1, the duration of vehicle door opening and closing, and the number of door opening and closing operations. Therefore, if these effects are not taken into account when calculating the estimated SOC, a situation may occur in which the charge level of the battery 11 becomes extremely insufficient while the vehicle 1 is in operation, making it impossible to automatically drive the vehicle 1 during operation. Therefore, in an embodiment of the present invention, the estimated SOC value is calculated taking these effects into account. This will be described next with reference to Figures 6A to 8.

[0023] First, referring to Figures 6A to 6C, the solid lines in Figures 6A to 6C show the time-dependent change in the estimated SOC calculated using the calculated value of the SOC decrease amount ΔSOC at each elapsed time t. In Figures 6A to 6C, the vertical axis represents the estimated SOC, and the horizontal axis represents the elapsed time t since vehicle 1 departed from garage 5. Also, on the vertical axis in Figures 6A to 6C, SOCA represents the battery charging rate at the time of full charging, and SOCX represents the allowable lower limit of SOC. On the horizontal axis in Figures 6A to 6C, BS1, BS2, BS3, and BS4 represent bus stops. Note that Figures 6A to 6C are shown diagrammatically for illustrative purposes, and actual estimated SOC values ​​change over time in a more complex manner. Hereinafter, the estimated SOC values ​​shown by the solid lines in Figures 6A to 6C will be referred to as reference estimated SOC values.

[0024] The dashed line in Figure 6A shows the change over time in the estimated SOC when several passengers board vehicle 1 at bus stop BS2 and several more passengers board vehicle 1 at bus stop BS3. Because the driving force required for vehicle 1 increases as the number of passengers increases, the SOC decrease amount ΔSOC increases as the number of passengers increases. In this case, in an embodiment of the present invention, as shown in Figure 7A, a correction coefficient K1 that increases in proportion to the number of passengers is calculated in advance. In a travel section where the number of passengers increases, the calculated SOC decrease amount ΔSOC at each elapsed time t is multiplied by the correction coefficient K1 to calculate the final SOC decrease amount ΔSOC at each elapsed time t. Therefore, as shown by the dashed line in Figure 6A, the estimated SOC changes over time while remaining lower than the reference estimated SOC value.

[0025] The dashed line in Figure 6B shows the change over time in the estimated SOC when traffic congestion occurs between bus stops BS2 and BS3. The greater the deceleration rate due to traffic congestion or the greater the number of repeated stops and starts, the higher the level of congestion is deemed to be. Therefore, the higher the level of congestion, the greater the power consumed to drive vehicle 1, and therefore the greater the SOC decrease ΔSOC. In this case, in an embodiment of the present invention, as shown in Figure 7B, a correction coefficient K2 that increases in proportion to the level of congestion is calculated in advance. For the travel section where traffic congestion occurs, the calculated SOC decrease ΔSOC at each elapsed time t is multiplied by the correction coefficient K2 to calculate the final SOC decrease ΔSOC at each elapsed time t. Therefore, as shown by the dashed line in Figure 6B, the estimated SOC changes over time while remaining lower than the reference estimated SOC value.

[0026] The dashed line in FIG. 6C shows the change over time in the estimated SOC when the air conditioner installed in the passenger compartment of vehicle 1 is operated. In this case, the greater the temperature difference ΔT between the air conditioner's set temperature and the outside air temperature, the greater the power consumed by the air conditioner's operation. Therefore, the greater the temperature difference ΔT between the air conditioner's set temperature and the outside air temperature, the greater the SOC drop ΔSOC. In this case, in an embodiment of the present invention, the SOC drop ΔSOCT caused by the air conditioner's operation is calculated separately from the SOC drop ΔSOC at each elapsed time t. As shown in FIG. 7C, the SOC drop ΔSOCT, which increases in proportion to the temperature difference ΔT between the air conditioner's set temperature and the outside air temperature, is calculated in advance. The estimated SOC is calculated by subtracting the calculated SOC drop ΔSOC and the SOC drop ΔSOCT at each elapsed time t from the battery charging rate SOCA at the end of charging. Therefore, as shown by the dashed line in FIG. 6C, the estimated SOC changes over time while remaining lower than the reference estimated SOC.

[0027] On the other hand, when a door of the vehicle 1 is opened or closed while the air conditioner is operating, the temperature inside the vehicle 1 drops if heating is in progress, and rises if cooling is in progress. In this case, the longer the vehicle 1 door is open, the greater the amount of temperature drop or rise inside the vehicle 1. The greater the amount of temperature drop or rise inside the vehicle 1, the greater the power consumption of the air conditioner to return the temperature inside the vehicle 1 to the set temperature. In this case, in an embodiment according to the present invention, as shown in FIG. 7D , a correction coefficient K3 that increases in proportion to the vehicle 1 door open time D is calculated in advance. When a vehicle 1 door is opened, the SOC drop ΔSOCT is multiplied by the correction coefficient K3 to calculate the final SOC drop ΔSOCT. Next, the SOC estimate is calculated by subtracting the calculated SOC drop ΔSOC at each elapsed time t and the final SOC drop ΔSOCT from the battery charging rate SOCA at the end of charging. Therefore, the longer the door opening time D of the vehicle 1, the lower the estimated value of the SOC, and the more frequently the door is opened and closed, the faster the rate at which the estimated value of the SOC drops.

[0028] As described above, the charging planning unit 42 shown in Fig. 4 creates a charging plan for determining a charging schedule for the battery 11 mounted on the vehicle 1. Fig. 8 shows a charging planning routine executed in the electronic control unit 17 of the vehicle 1 to create this charging plan. This charging planning routine is executed, for example, before the vehicle 1 starts traveling.

[0029] Referring to FIG. 8 , first, in step 60, it is determined whether fixed-time, fixed-route service or on-demand service is being performed. If fixed-time, fixed-route service is being performed, the process proceeds to step 61, where the predicted number of passengers is acquired. In an embodiment according to the present invention, data relating to the number of passengers by day of the week and hourly rate detected by the passenger authentication unit 41 (FIG. 4) of the vehicle 1 is stored in the memory 20 of the electronic control unit 17. In step 61, the number of passengers is predicted based on this data. Next, in step 62, fixed-time, fixed-route service information is acquired. In an embodiment according to the present invention, in the memory 35 of the electronic control unit 31 of the fleet management server 3, operation information such as the route from the depot 5 to the turnaround point, the operating speed, bus stops, the predicted door opening time D of the vehicle 1 at each bus stop, and the time of first departure from the depot 5 is pre-stored. In step 62, this operation information is acquired from the fleet management server 3.

[0030] Next, in step 63, the degree of traffic congestion on the travel route of vehicle 1 is calculated. In this embodiment of the present invention, the regional information unit 52 of the regional information management server 4 acquires event information in the region through which vehicle 1 travels and information regarding the degree of congestion in the region through which vehicle 1 travels, and in step 63, the degree of congestion on the travel route of vehicle 1 is calculated based on this information. Next, in step 64, the SOC decrease amount ΔSOC at each elapsed time t is calculated based on the operation information acquired from the traffic management server 3. Next, in step 65, a correction coefficient K1 is calculated from the number of passengers predicted in step 61 using the relationship shown in FIG. 7A, and a correction coefficient K2 is calculated from the degree of congestion calculated in step 63 using the relationship shown in FIG. 7B.

[0031] Next, in step 66, the SOC decrease amount ΔSOC at each elapsed time t calculated in step 64 is multiplied by correction coefficients K1 and K2 to calculate the final SOC decrease amount ΔSOC at each elapsed time t. Next, in step 67, the SOC decrease amount ΔSOCT is calculated from the temperature difference ΔT between the air conditioner's set temperature and the outside air temperature using the relationship shown in Figure 7C. Next, in step 68, the vehicle door open time D predicted at each bus stop is obtained based on the operation information obtained from the operation management server 3. Next, in step 69, a correction coefficient K3 is calculated from the vehicle door open time D using the relationship shown in Figure 7D.

[0032] Next, in step 70, the estimated SOC at each elapsed time t is calculated by subtracting the calculated final SOC decrease ΔSOC at each elapsed time t and the calculated final SOC decrease ΔSOCT from the battery charging rate SOCA at the time of charging completion, and further subtracting the SOC decrease (K3·ΔSOCT) due to the vehicle door opening and closing action at each bus stop before each elapsed time t. In this manner, the change in the estimated SOC over time is calculated. Once the change in the estimated SOC over time is calculated, in step 71, a charging schedule is created so that the battery 11 of the vehicle 1 can be charged by the charging equipment 6 before the estimated SOC decreases to the allowable lower limit SOCX.

[0033] On the other hand, if it is determined in step 60 that on-demand operation is being performed, the process proceeds to step 72, where the number of passengers is acquired. In an embodiment according to the present invention, the reservation unit 51 of the operations management server 3 stores the number of passengers and other information for which reservations have been accepted, and an operation plan based on the reservation details is created in the operation planning unit 50. In step 72, the number of passengers is acquired from the reservation unit 51 of the operations management server 3. Next, in step 73, operation information such as the operation route from the garage 5 to the destination, the operating speed, bus stops, the predicted door opening time D of the vehicle 1 at the bus stop, and the time of initial departure from the garage 5 is acquired from the operation planning unit 50 of the operations management server 3. Next, in step 74, the degree of traffic congestion on the operation route of the vehicle 1 is calculated, and the process proceeds to step 64.

[0034] In this case, as in the case of fixed-time, fixed-route operation, a charging schedule is created in step 71 so that the battery 11 of the vehicle 1 can be charged by the charging equipment 6 before the estimated SOC value drops to the allowable lower limit SOCX. In this way, if the SOC is estimated taking into consideration the number of passengers in the vehicle 1, the degree of congestion, the operation of the air conditioner installed in the vehicle 1, the door opening time D of the vehicle 1, and the number of door opening and closing operations, the battery 11 can be charged at an appropriate time, and an efficient charging schedule can be achieved.

[0035] As described above, in an embodiment of the present invention, in a vehicle 1 that can switch from autonomous driving to manual driving, a battery charging rate SOC that changes over time due to power consumption is estimated when the vehicle 1 is in autonomous driving. In this case, the battery charging rate SOC that changes over time is estimated based on the operating state of the vehicle 1, and a charging schedule is created based on the estimated value of the battery charging rate SOC. Also, in an embodiment of the present invention, the battery charging rate is estimated based on one or both of the operating environment of the air conditioner installed in the vehicle 1 and the open / closed state of the doors of the vehicle 1, in addition to the operating state of the vehicle 1. In this case, the battery charging rate SOC is further estimated based on one or both of the number of passengers in the vehicle 1 and the degree of congestion of the road on which the vehicle 1 is traveling. Also, in this case, the operating environment of the air conditioner is the temperature difference ΔT between the set temperature in the passenger compartment 1 and the outside air temperature, and the open / closed state of the vehicle doors is the door opening time and the number of times the doors are opened and closed.

[0036] However, even if the charging system is configured to charge the battery 11 at an appropriate time, there are cases where the actual charging rate of the battery 11 falls significantly below the estimated battery charging rate during autonomous driving of the vehicle 1. If the actual charging rate of the battery 11 falls significantly below the estimated battery charging rate, it becomes impossible to continue autonomous driving, which consumes a lot of power, before the vehicle 1 reaches the garage 5 where the charging equipment 6 is installed, and there is an increased risk that the vehicle 1 will stop mid-travel. Therefore, in an embodiment according to the present invention, when the actual charging rate of the battery 11 falls significantly below the estimated battery charging rate, the vehicle 1 is configured to switch from autonomous driving to manual driving, which consumes less power, so as to prevent the vehicle 1 from stopping mid-travel.

[0037] This will be explained next with reference to Figures 9 and 10. Figure 9 shows a routine for calculating the actual state of charge (SOC) of the battery 11, which is executed in the electronic control unit 17 of the vehicle 1. This calculation routine is executed by interruption at regular intervals. 9, first, in step 80, the amount of current flowing into the battery 11 within a certain time period, ΔI, is read. Next, in step 81, the product of the amount of current flowing into the battery 11 within the certain time period, ΔI, and a constant C is added to the actual SOC. Note that when current flows out of the battery 11, the amount of current flowing into the battery 11, ΔI, becomes negative. Note that this method of calculating the actual SOC is merely an extremely simple example, and various known methods of calculating the actual SOC can be used.

[0038] 10 shows a routine for executing a driving mode switching measure executed in the electronic control unit 17 by the manual driving mode switching section 45 of the vehicle 1. This routine is executed by interruption at regular intervals. 10, first, in step 90, the current actual SOC calculated in the actual SOC calculation routine shown in Fig. 9 is set to X. Next, in step 91, the estimated value of the current SOC calculated in step 70 of the charge control routine shown in Fig. 8 is set to Y. Next, in step 92, it is determined whether the actual SOCX has decreased below the estimated SOC value Y by a predetermined value α or more.

[0039] If it is determined in step 92 that the actual SOCX is not lower than the estimated SOC value Y by a predetermined value α or more, the process proceeds to step 94, where it is determined whether the actual SOCX is lower than the estimated SOC value Y by a predetermined value β or more. Note that this predetermined value β is smaller than the predetermined value α. If it is determined in step 94 that the actual SOCX is not lower than the estimated SOC value Y by the predetermined value β or more, the process cycle ends. In this case, the vehicle 1 continues to operate autonomously.

[0040] On the other hand, if it is determined in step 92 that the actual SOCX has dropped below the estimated SOC value Y by a predetermined value α or more, it is determined that if the operation of the vehicle 1 in the automatic driving mode continues, there is a risk that the vehicle 1 will stop mid-travel, and the process proceeds to step 93, where a manual driving switching measure is executed to switch the vehicle 1 from automatic driving to manual driving. When this manual driving switching measure is executed, for example, the driver of the vehicle 1, who is on board for safety reasons, is notified by the notification device 26 that the operation will be switched from automatic driving to manual driving, and when the driver confirms this notification, the driver switches the operation of the vehicle 1 from automatic driving to manual driving. Alternatively, when this manual driving switching measure is executed, the passenger of the vehicle 1 is notified by the notification device 26 that the operation will be switched from automatic driving to manual driving, the vehicle 1 is temporarily stopped on the side of the road, and then the driver manually drives the vehicle 1. In either case, when the manual driving switching measure is executed in step 93, the vehicle 1 is switched from automatic driving to manual driving.

[0041] On the other hand, when it is determined in step 94 that the actual SOCX is lower than the estimated SOC Y by the predetermined value β or more, that is, when it is determined that the actual SOCX is not lower than the estimated SOC Y by the predetermined value α or more but is lower than the estimated SOC Y by the predetermined value β or more, the process proceeds to step 95, where power consumption reduction measures are taken to reduce the power consumption of the battery 11 as much as possible in order to continue autonomous driving as long as possible. For example, measures are taken to reduce the power consumption of the battery 11 as much as possible by switching the air conditioner installed in the vehicle 1 to an energy-saving mode. In addition, measures are taken to keep the doors of the vehicle 1 closed as much as possible, such as not opening the doors at bus stops where there are no passengers getting on or off, and closing the doors immediately after passengers have finished getting on or off.

[0042] Thus, in an embodiment of the present invention, in a vehicle 1 that can be switched from automatic driving to manual driving, the vehicle 1 is equipped with a battery 11 and a processor 17, and the processor 17 estimates the battery charging rate that changes over time due to power consumption when the vehicle 1 is being driven automatically, obtains the actual charging rate of the battery when the vehicle is being driven automatically, and when the actual charging rate of the battery drops below the estimated battery charging rate by more than a predetermined value during automatic driving, the vehicle is switched from automatic driving to manual driving.

[0043] In this case, in an embodiment according to the present invention, the predetermined values ​​are a first predetermined value α and a second predetermined value β that is smaller than the first predetermined value α, and when, during automatic driving, the actual charging rate X of the battery 11 falls below the estimated battery charging rate Y by the first predetermined value α or more, the automatic driving is switched to manual driving, and when, during automatic driving, the actual charging rate X of the battery 11 does not fall below the estimated battery charging rate Y by the first predetermined value α or more but falls by the second predetermined value β or more, measures to reduce battery power consumption are taken without switching to manual driving. In this case, the measures to reduce battery power consumption include one or both of switching the air conditioner installed in the vehicle 1 to an energy saving mode and keeping the doors of the vehicle 1 closed as much as possible. [Explanation of symbols]

[0044] 1 vehicle 3. Traffic management server 4. Regional information management server 10 Vehicle drive unit 11 Battery 17 Electronic Control Unit

Claims

1. A vehicle that can be switched from automatic driving to manual driving is provided with a battery and a processor, and the processor Estimate the battery charge rate that changes over time due to power consumption when the vehicle is being driven autonomously, Obtain the actual battery charge rate when autonomous driving is in progress, A vehicle control device that switches from autonomous driving to manual driving when the actual battery charging rate drops below an estimated battery charging rate by more than a predetermined value during autonomous driving.

2. 2. The vehicle control device according to claim 1, wherein the predetermined values ​​comprise a first predetermined value and a second predetermined value smaller than the first predetermined value, and wherein the processor switches from automatic driving to manual driving when, during automatic driving, the actual charging rate of the battery drops below the estimated battery charging rate by the first predetermined value or more, and takes measures to reduce battery power consumption without switching to manual driving when, during automatic driving, the actual charging rate of the battery does not drop below the estimated battery charging rate by the first predetermined value or more but drops below the second predetermined value or more.

3. 3. The vehicle control device according to claim 2, wherein the measure to reduce battery power consumption comprises one or both of switching an air conditioner installed in the vehicle to an energy saving mode and keeping the vehicle doors closed as much as possible.

4. 2. The vehicle control device according to claim 1, wherein the processor estimates a battery charging rate that changes over time based on the operating state of the vehicle, and creates a charging schedule based on the estimated battery charging rate.

5. 5. The vehicle control device according to claim 4, wherein the processor estimates the battery charging rate based on the vehicle's operating state as well as one or both of the operating environment of an air conditioner installed in the vehicle and the open / close state of the vehicle's doors.

6. The vehicle control device according to claim 5 , wherein the processor further estimates the battery charging rate based on one or both of the number of passengers in the vehicle and the degree of congestion on the road on which the vehicle travels.

7. 6. The vehicle control device according to claim 5, wherein the operating environment of the air conditioner is a temperature difference between a set temperature in the vehicle interior and an outside temperature, and the vehicle door opening / closing state is a door opening time and a number of times the door is opened and closed.

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