Electric vehicles and control devices

Abstract

This invention provides a technology for electric vehicles that have an on-demand mode that simulates the feel of operating a virtual mobility device, and that can reduce the driver's difficulty after switching to the simulated virtual mobility device. [Solution] The electric vehicle is equipped with one or more processors that control the output of the electric motor. When the electric vehicle is in on-demand mode, one or more processors use an on-demand model to calculate the virtual acceleration of the virtual mobility in response to the driver's driving operations and control the output of the electric motor so that the acceleration of the electric vehicle is the virtual acceleration. Furthermore, when the virtual mobility to be reproduced is switched to a second virtual mobility, one or more processors control the output of the electric motor in a transition mode that gradually changes at least a portion of the driving environment characteristics simulated by the on-demand model to the characteristics of the second virtual mobility.

Description

Technical Field

[0001] The present disclosure relates to an electric vehicle having an electric motor as a drive source.

Background Art

[0002] An electric motor can be controlled to output a desired motor torque by controlling the applied voltage and field excitation. Utilizing this, a technique of reproducing various driving environments in an electric vehicle by appropriately controlling the electric motor of the electric vehicle has been considered. For example, Patent Document 1 discloses an electric vehicle capable of pseudo-reproducing a manual shifting operation of a manual transmission vehicle. Patent Document 1 also discloses displaying the rotational speed of a virtual engine on a display device and outputting an engine sound simulating the sound of an engine type selected from a plurality of types from a speaker.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Preferences for driving environments vary among drivers. Also, a driver may want to enjoy various mobility driving environments according to their mood. Therefore, the inventors of the present disclosure are considering an "on-demand mode" in which the driving environments of a plurality of virtual mobilities are pseudo-reproduced in one electric vehicle using a plurality of models that model the plurality of virtual mobilities. In the on-demand mode, the electric motor is controlled so as to reproduce the operation feeling when a virtual mobility selected from a plurality of virtual mobilities is driven in the electric vehicle.

[0005] Consider a scenario where an electric vehicle is in on-demand mode and the driver switches between the virtual mobility options being simulated. Depending on the patterns of the virtual mobility options before and after the switch, the feel of the operation may change significantly. In such cases, it may be difficult for the driver to immediately adapt to the feel of the new virtual mobility option. As a result, the driver may experience stress or become complacent about safe driving.

[0006] This disclosure has been made in view of the above-mentioned issues. One objective of this disclosure is to provide a technology that can reduce the difficulties faced by drivers after switching to virtual mobility. [Means for solving the problem]

[0007] The first aspect of this disclosure relates to an electric vehicle having an electric motor as a power source. The electric vehicle comprises a driving control member used for driving, one or more memory devices, and one or more processors that control the output of the electric motor. One or more memory devices manage multiple on-demand models that model multiple virtual mobilitys with different driving environment characteristics in response to the driver's driving operations. When the electric vehicle is in on-demand mode, one or more processors obtain from one or more memory devices a target on-demand model corresponding to a target virtual mobility selected from the multiple virtual mobilitys, calculate the virtual acceleration of the target virtual mobility in response to the driver's driving operations using the target on-demand model based on the operating state of the driving control member and the driving state of the electric vehicle, and control the output of the electric motor so that the acceleration of the electric vehicle is the virtual acceleration. Furthermore, when the target virtual mobility is switched from the first virtual mobility to the second virtual mobility, one or more processors control the output of the electric motor in a transition mode that gradually changes at least a portion of the driving environment characteristics simulated by the target on-demand model to the characteristics of the second virtual mobility.

[0008] A second aspect of this disclosure relates to a control device for an electric vehicle having an electric motor as a drive source. The electric vehicle is equipped with driving controls used for driving. The control device comprises one or more memory devices and one or more processors that control the output of the electric motor. One or more memory devices manage multiple on-demand models that model multiple virtual mobilitys with different driving environment characteristics in response to the driver's driving operations. When the electric vehicle is in on-demand mode, one or more processors obtain from one or more memory devices a target on-demand model corresponding to a target virtual mobility selected from the multiple virtual mobilitys, calculate the virtual acceleration of the target virtual mobility in response to the driver's driving operations using the target on-demand model based on the operating state of the driving controls and the driving state of the electric vehicle, and control the output of the electric motor so that the acceleration of the electric vehicle is the virtual acceleration. Furthermore, when the target virtual mobility is switched from the first virtual mobility to the second virtual mobility, one or more processors control the output of the electric motor in a transition mode that gradually changes at least a portion of the driving environment characteristics simulated by the target on-demand model to the characteristics of the second virtual mobility. [Effects of the Invention]

[0009] According to this disclosure, when the target virtual mobility is switched, the output of the electric motor is controlled in transition mode. In transition mode, at least a portion of the driving environment characteristics of the target on-demand model are gradually changed to the characteristics of the second virtual mobility. This makes it possible to suppress a large change in the feel of operation after switching the target virtual mobility. As a result, it is possible to reduce the driver's difficulty after switching the target virtual mobility. [Brief explanation of the drawing]

[0010] [Figure 1] This is a diagram showing the configuration of an electric vehicle according to an embodiment. [Figure 2] This is a tree diagram showing an example of a selection input accepted by the HMI regarding the control mode of an electric vehicle according to the embodiment. [Figure 3]This figure shows an example of the functional configuration of a control device that functions as a drive control device. [Figure 4] This figure shows an example of the acceleration characteristics of a target virtual mobility device reproduced using an electric vehicle. [Figure 5] This figure shows an example of the functional configuration of the on-demand mode calculation unit. [Figure 6] This figure shows an example of the functionality of the transition mode related to the first specific example. [Figure 7] This figure shows an example of the functionality of the transition mode related to the second specific example. [Figure 8] This is a flowchart showing the processing flow for determining the transition mode. [Figure 9] This is a flowchart showing the processing flow related to determining the conditions for initiating the migration. [Figure 10] This flowchart shows the processing flow related to determining the conditions for completing the migration. [Figure 11] This figure shows an example of the transition mode determination process. [Figure 12] This figure shows an example of the configuration of an on-demand model. [Figure 13] This figure shows an example of the functional configuration of a control device that functions as an in-vehicle equipment control device. [Modes for carrying out the invention]

[0011] Embodiments of this disclosure will be described below with reference to the drawings. In each drawing, the same or corresponding parts are denoted by the same reference numerals, and their descriptions are simplified or omitted.

[0012] 1. Configuration of the powertrain of an electric vehicle Figure 1 is a schematic diagram showing the configuration of an electric vehicle 100 according to an embodiment of this disclosure. First, the configuration of the power system of the electric vehicle 100 will be described with reference to Figure 1.

[0013] The electric vehicle 100 is equipped with an electric motor (M) 2 as a drive source for propulsion. The electric motor 2 is, for example, a three-phase AC motor. An inverter (INV) 16 is attached to the electric motor 2. The output shaft of the electric motor 2 is connected to the propeller shaft 5 via a reduction gear (not shown). The propeller shaft 5 is connected to a differential gear 6. The differential gear 6 is connected to the left and right drive wheels 8 by left and right drive shafts 7. The drive wheels may be the front wheels or the rear wheels.

[0014] The inverter 16, electric motor 2, reduction gear, and differential gear 6 may be integrally configured as an e-axle. In this case, the electric vehicle 100 does not have a propeller shaft 5, and the e-axle is connected to the drive shaft 7. Another variation is that the configuration of the electric vehicle 100 may be four-wheel drive. For example, the electric vehicle 100 may have a transfer case connected to the electric motor 2, and the transfer case may be configured to distribute the output of the electric motor 2 to the front and rear wheels. Alternatively, for example, the front drive shaft 7 and the rear drive shaft 7 may each be configured to have an e-axle.

[0015] The inverter 16 is connected to the battery (BATT) 14. The inverter 16 is, for example, a voltage-type inverter that controls the motor torque of the electric motor 2 by PWM control. In other words, the electric vehicle 100 is a battery electric vehicle (BEV) that runs on the electric motor 2 as a driving source and on the electrical energy stored in the battery 14.

[0016] 2. Configuration of the control system of an electric vehicle Next, we will explain the configuration of the control system of the electric vehicle 100 with reference to Figure 1.

[0017] The electric vehicle 100 is equipped with a vehicle speed sensor 30. The vehicle speed sensor 30 outputs a signal indicating the vehicle speed of the electric vehicle 100. At least one of the wheel speed sensors (not shown), which are provided on each of the left and right front wheels and the left and right rear wheels, is used as the vehicle speed sensor 30.

[0018] The electric vehicle 100 is equipped with an accelerator position sensor 32. The accelerator position sensor 32 is located on the accelerator pedal 22 and outputs a signal indicating the operating state of the accelerator pedal 22. The operating state of the accelerator pedal 22 typically includes the accelerator opening degree and the accelerator opening speed. Alternatively, the electric vehicle 100 may be equipped with a lever-type or dial-type accelerator control device operated by hand instead of the accelerator pedal 22. In this case as well, the accelerator position sensor 32 outputs a signal indicating the operating state of these accelerator control devices.

[0019] The electric vehicle 100 is equipped with a brake position sensor 34. The brake position sensor 34 is located on the brake pedal 24 and outputs a signal indicating the operating state of the brake pedal 24. The operating state of the brake pedal 24 typically includes the brake opening degree and the brake opening speed.

[0020] The accelerator pedal 22 and the brake pedal 24 are each one of the driving operation members used to drive the electric vehicle 100. The electric vehicle 100 according to this embodiment is further equipped with a simulated paddle shifter 25, a simulated H-type shifter 26, and a simulated clutch pedal 27 as driving operation members. The simulated paddle shifter 25, the simulated H-type shifter 26, and the simulated clutch pedal 27 are driving operation members (hereinafter referred to as "simulated gear shift operation members") that simulate operation members used for gear shifting in a vehicle equipped with a manual gear shifting transmission (hereinafter simply referred to as "manual gear shifting vehicle").

[0021] The simulated paddle shifter 25 simulates a paddle shifter, which is a type of sequential shifter. The simulated paddle shifter 25 has a structure similar to a shift paddle attached to the steering wheel or steering shaft, and the left and right paddles can be moved independently. The simulated paddle shifter 25 is equipped with a shift switch 35. The shift switch 35 outputs a signal indicating the operating status of the simulated paddle shifter 25. Specifically, the shift switch 35 outputs an upshift signal when either the left or right paddle is pulled, and outputs a downshift signal when the other paddle is pulled.

[0022] In this embodiment, the electric vehicle 100 may be configured to have a lever-type or dial-type sequential shifter instead of, or in addition to, the pseudo-paddle shifter 25. In this case as well, the shift switch 35 outputs an upshift signal and a downshift signal according to the operating state of the sequential shifter.

[0023] The pseudo-H-type shifter 26 simulates an H-type shifter. The pseudo-H-type shifter 26 has a structure similar to a shift stick provided on the console and can move along an H-shaped gate between shift positions. The pseudo-H-type shifter 26 is equipped with a shift position sensor 36. The shift position sensor 36 outputs a signal indicating the selected shift position as the operating state of the pseudo-H-type shifter 26. For example, the shift positions selectable by the pseudo-H-type shifter 26 are neutral, 1st, 2nd, 3rd, 4th, 5th, and 6th.

[0024] The pseudo-H-type shifter 26 may be configured to function as a selector for selecting the shifts of the electric vehicle 100 (e.g., D (Drive), P (Parking), R (Reverse), N (Neutral)). For example, each shift position selected by the pseudo-H-type shifter 26 may be configured to correspond to each shift of the electric vehicle 100. Alternatively, the pseudo-H-type shifter 26 may be configured to have additional shift positions for selecting the shifts of the electric vehicle 100. The electric vehicle 100 may also have a selector separate from the pseudo-H-type shifter 26.

[0025] The simulated clutch pedal 27 has a structure similar to the clutch pedal found in conventional manual transmission vehicles. For example, the simulated clutch pedal 27 is equipped with a reaction force mechanism that generates a reaction force in response to the driver's depressing. The position when no force is applied is the starting position of the simulated clutch pedal 27, and the position when it is fully depressed is the ending position of the simulated clutch pedal 27. The driver can operate the simulated clutch pedal 27 from the starting position to the ending position, resisting the reaction force from the reaction force mechanism. The simulated clutch pedal 27 is equipped with a clutch position sensor 37. The clutch position sensor 37 outputs a signal indicating the operating state of the simulated clutch pedal 27. The operating state of the simulated clutch pedal 27 typically includes the amount of depression of the simulated clutch pedal 27.

[0026] In this embodiment, the simulated clutch pedal 27 is a pedal-type driving operation member operated by the foot. However, the electric vehicle 100 may be configured to have a lever-type or dial-type simulated clutch operating device operated by hand instead of the simulated clutch pedal 27. The simulated clutch operating device may be configured to allow the driver to operate it from the starting position to the ending position against the reaction force, similar to the simulated clutch pedal 27. The simulated clutch operating device can employ various structures that allow the driver to experience the feel of operating a clutch pedal, similar to that of a conventional manual transmission vehicle, using their feet or hands.

[0027] As described above, the driving control members of the electric vehicle 100 according to this embodiment include the simulated gear shifting control members described above, compared to a normal BEV. As will be described later, the electric vehicle 100 according to this embodiment has an "on-demand mode" as a control mode that reproduces the driving environment characteristics of a virtual mobility selected from among a plurality of virtual mobilitys. The simulated gear shifting control members described above are driving control members that are mainly used when the electric vehicle 100 is in on-demand mode. In particular, when the electric vehicle 100 is in on-demand mode, the driving control members used for driving operations are switched according to the virtual mobility to be reproduced. Alternatively, the function of each driving control member is switched according to the virtual mobility to be reproduced. When the electric vehicle 100 is not in on-demand mode, the simulated gear shifting control members described above may be configured not to function. However, even when the electric vehicle 100 is not in on-demand mode, some function may be provided to the operation of the simulated gear shifting control members. For example, the simulated paddle shifter 25 may be used to set the strength of the regenerative braking.

[0028] In addition, the electric vehicle 100 may be equipped with various driving control components, such as a steering wheel, for steering. Furthermore, the electric vehicle 100 may be equipped with special driving control components that are used when a specific virtual mobility is selected. For example, the electric vehicle 100 may be equipped with a control panel having multiple switches.

[0029] The electric vehicle 100 is equipped with a rotational speed sensor 40. The rotational speed sensor 40 is installed on the electric motor 2 and outputs a signal indicating the rotational speed of the electric motor 2.

[0030] The electric vehicle 100 is equipped with a battery management system (BMS) 10. The battery management system 10 is a device that monitors the cell voltage, current, temperature, etc., of the battery 14. In particular, the battery management system 10 has a function to estimate the charge state (SOC) of the battery 14.

[0031] The electric vehicle 100 is equipped with a human-machine interface (HMI) 20. The HMI 20 presents various information to the driver through displays and sounds, and also accepts various inputs from the driver. The HMI 20 consists of a display (e.g., multi-information display, meter display, multimedia display), a touchscreen, switches (e.g., steering wheel switches, multimedia switches, door switches), a touchpad, a speakerphone, a microphone, etc. For example, the HMI 20 displays various information on the display and accepts input from the driver regarding the displayed content through touch operations on the touchscreen.

[0032] The electric vehicle 100 is equipped with a speaker 11. The speaker 11 includes at least an in-vehicle speaker that generates sound inside the cabin of the electric vehicle 100. As another example, the speaker 11 may also include an external speaker that generates sound outside the electric vehicle 100. The electric vehicle 100 may have both an in-vehicle speaker and an external speaker as the speaker 11. The speaker 11 may be configured as part of the HMI 20. The output of the speaker 11 is controlled by a control device 101, which will be described later.

[0033] The electric vehicle 100 is equipped with an instrument cluster 13. The instrument cluster 13 displays various types of information. Examples of instruments 13 include a speedometer, odometer, tachometer, trip meter, battery level indicator, etc. The instrument cluster 13 may also be configured as part of the HMI 22. The display of the instrument cluster 13 is controlled by the control device 101, which will be described later.

[0034] The electric vehicle 100 is equipped with a control device 101. Various sensors and controlled devices mounted on the electric vehicle 100 are connected to the control device 101 via an in-vehicle network such as a control area network (CAN). In addition to the vehicle speed sensor 30, accelerator position sensor 32, brake position sensor 34, and rotational speed sensor 40, various other sensors may be mounted on the electric vehicle 100 and connected to the control device 101 via the in-vehicle network.

[0035] The control device 101 generates control signals for various controls of the electric vehicle 100 based on signals acquired from each sensor. The control device 101 is typically an electronic control unit (ECU). The control device 101 may be a combination of multiple ECUs. The control device 101 comprises one or more processors 102 (hereinafter simply referred to as processor 102) and one or more storage devices 103 (hereinafter simply referred to as storage devices 103).

[0036] The processor 102 performs various processes. The processor 102 consists of, for example, a general-purpose processor, a special-purpose processor, a CPU (central processing unit), a GPU (graphics processing unit), an ASIC (application-specific integrated circuit), an FPGA (field-programmable gate array), an integrated circuit, a conventional circuit, and one or more combinations thereof. The processor 102 can also be called processing circuitry. Processing circuitry is hardware programmed to realize the functions of the control device 101, or hardware that performs the functions of the control device 101.

[0037] The storage device 103 stores various information necessary for the execution of processing by the processor 102. The storage device 103 is composed of recording media such as RAM (random access memory), ROM (read-only memory), SSD (solid state drive), HDD (hard disk drive), etc. The storage device 103 stores a computer program 104 that can be executed by the processor 102 and various data 105. The computer program 104 consists of multiple instruction codes that describe the processing to be executed by the processor 102. The computer program 104 is recorded on a computer-readable recording medium. The functions of the control device 101 are realized through the cooperation of the processor 102, which executes the computer program 104, and the storage device 103.

[0038] The control device 101 according to this embodiment has at least two control modes for controlling the electric vehicle 100: a normal mode and an on-demand mode. Depending on the selected control mode, the control of the electric vehicle 100 performed by the control device 101 changes. The control modes of the electric vehicle 100 will be described below.

[0039] 3. Control modes for electric vehicles As described above, the electric vehicle 100 has at least two control modes: a normal mode and an on-demand mode. The normal mode is a control mode in which the electric vehicle 100 is controlled to operate as a normal BEV. On the other hand, the on-demand mode is a control mode in which the electric vehicle 100 reproduces the driving environment characteristics of a virtual mobility selected from among several virtual mobility options (hereinafter referred to as the "target virtual mobility"). When the electric vehicle 100 is in on-demand mode, the control device 101 controls the electric vehicle 100 so that the driver can obtain a driving environment as if they were driving the target virtual mobility. In particular, the driving environment characteristics of the target virtual mobility reproduced in on-demand mode include the acceleration characteristics of the virtual mobility in response to the driver's driving operations. Details of the control of the electric vehicle 100 in each of the normal mode and on-demand mode will be described later.

[0040] In on-demand mode, multiple virtual mobility options include various mobility options with different driving environment characteristics in response to driver input. "Mobility" is a general term for vehicles that can be driven by the driver operating driving controls. Virtual mobility options are typically vehicles with different driving environment characteristics than electric vehicles (100). However, virtual mobility options may also be various forms of vehicles such as motorcycles or trains. Each virtual mobility option may be based on a real-world mobility option, or it may be based on a mobility option that does not exist in reality. Differences in acceleration characteristics as driving environment characteristics generally stem from differences in the powertrain configuration from the drive source to the drive wheels and differences in powertrain control methods. Therefore, multiple virtual mobility options can be considered to include various mobility options with at least some differences in powertrain-related configurations and control methods. For simplicity, in the following explanation, each virtual mobility option will be assumed to be a vehicle.

[0041] The control mode is selected by the driver operating the HMI20. The HMI20 is configured to accept input from the driver to select the control mode. Furthermore, with respect to the on-demand mode, the HMI20 is configured to accept input from the driver to select the target virtual mobility.

[0042] Figure 2 is a tree diagram showing an example of selection input accepted by the HMI20. For example, the HMI20 accepts selection input from the driver via the display or touchscreen, following the tree shown in Figure 2.

[0043] First, the HMI20 displays a settings menu screen on the display or touchscreen according to the driver's input. The initial settings menu screen displays the options "Control Mode" and "Target Virtual Mobility". The "Control Mode" option is for accepting input from the driver to select the control mode. The "Target Virtual Mobility" option is for accepting input from the driver to select the target virtual mobility.

[0044] When the "Control Mode" option is selected, the settings menu screen then displays the options "Normal Mode" and "On-Demand Mode". If "Normal Mode" is selected, the HMI20 determines that the control mode of the electric vehicle 100 is Normal Mode. If "On-Demand Mode" is selected, the HMI20 determines that the control mode of the electric vehicle 100 is On-Demand Mode. In this way, the HMI20 accepts the driver's input for selecting the control mode.

[0045] On the other hand, once the "Target Virtual Mobility" option is selected, the settings menu screen will then display the options "AT" and "MT". The "AT" and "MT" options represent classifications of the multiple virtual mobility vehicles that can be selected in on-demand mode, respectively. AT refers to vehicles equipped with an automatic transmission (AT). MT refers to vehicles equipped with a manual transmission (MT).

[0046] When the option "AT" is selected, the settings menu screen then displays the options "Virtual Mobility A1", "Virtual Mobility A2", and "Virtual Mobility B1". Virtual Mobility A1, Virtual Mobility A2, and Virtual Mobility B1 are virtual mobility options classified as AT from among the multiple selectable virtual mobility options. Similarly, when the option "MT" is selected, the settings menu screen then displays the options "Virtual Mobility C1" and "Virtual Mobility C2". Virtual Mobility C1 and Virtual Mobility C2 are virtual mobility options classified as MT from among the multiple selectable virtual mobility options. When any of these options is selected, the HMI20 determines that the selected virtual mobility is the target virtual mobility option. For example, if the option "Virtual Mobility A2" is selected, the HMI20 determines that Virtual Mobility A2 is the target virtual mobility option. In this way, the HMI20 accepts the driver's input for selecting the target virtual mobility option.

[0047] In the above description, the classification of multiple virtual mobility vehicles is merely an example, and the classification options may be changed as appropriate. For example, the classification options may further include an option indicating a vehicle equipped with a continuously variable transmission (CVT). Alternatively, the classification options may also indicate other classifications, such as classifications related to the type of drive system (e.g., internal combustion engine vehicle, hybrid vehicle, plug-in hybrid vehicle, fuel cell vehicle, battery electric vehicle), classifications related to the type of power source installed (e.g., inline 4 turbocharged engine, flat 6 engine, V12 engine, battery, fuel cell), or classifications related to the driving operation pattern (e.g., presence or absence of clutch operation, presence or absence of paddle shift operation). Furthermore, the classification options may be composed of multiple levels. For example, after a classification related to the type of transmission has been selected, the settings menu screen may display options related to the classification pattern. Alternatively, the settings menu screen may display a list of virtual mobility options without displaying the classification options.

[0048] Furthermore, the names displayed on the settings menu screen for each option may be appropriately chosen to facilitate driver understanding. For example, for options related to virtual mobility, the displayed names may be specific, such as vehicle type or product name, to help the driver visualize the virtual mobility.

[0049] As explained above, the driver can select a control mode by operating the HMI 20. The control device 101 controls the electric vehicle 100 according to the selected control mode.

[0050] The control device 101 according to this embodiment functions as a drive control device that controls the drive of the electric vehicle 100 by controlling the output of the electric motor 2 in accordance with the driver's driving operations. Specifically, the control device 101 functions as a drive control device when the processor 102 executes a computer program 104 for drive control stored in the storage device 103. The control of the electric vehicle 100 by the drive control device will be described below.

[0051] 4. Drive control device Figure 3 shows an example of the functional configuration of the drive control device 101a. The drive control device 101a calculates the target driving force TF of the electric vehicle 100 according to the driver's driving operations. The drive control device 101a then controls the output of the electric motor 2 to achieve the calculated target driving force TF.

[0052] The drive control device 101a receives signals from the HMI 20 and the sensor system 50. The sensor system 50 includes a vehicle speed sensor 30, an accelerator position sensor 32, a brake position sensor 34, a shift switch 35, a shift position sensor 36, a clutch position sensor 37, a rotational speed sensor 40, and a battery management system 10. The sensor system 50 may further include a steering angle sensor for detecting the steering angle of the steering wheel, a yaw rate sensor for detecting the yaw rate of the electric vehicle 100, an IMU (inertial measurement unit) for detecting the attitude of the electric vehicle 100, and sensors for detecting the surrounding environment of the electric vehicle 100 (e.g., a camera, radar, LiDAR), etc.

[0053] The signals input from the HMI 20 to the drive control device 101a include a signal indicating the control mode selected by the driver and a signal indicating the target virtual mobility selected by the driver. The signals input from the sensor system 50 to the drive control device 101a include signals indicating the operating status of the driving operation members (e.g., accelerator pedal 22, brake pedal 24, simulated paddle shifter 25, simulated H-type shifter 26, simulated clutch pedal 27) and signals indicating the driving status of the electric vehicle 100 (e.g., vehicle speed, battery 14 charge status (SOC: state of charge)).

[0054] The drive control device 101a includes, as functional blocks, a mode information acquisition unit 110, a normal mode calculation unit 120, an on-demand mode calculation unit 130, an arbitration unit 140, and an electric motor control unit 150. These functional blocks are realized through the cooperation of a processor 102 that executes a computer program 104 and a storage device 103.

[0055] The mode information acquisition unit 110 receives a signal from the HMI 20 and acquires information on whether normal mode or on-demand mode is selected. The mode information acquisition unit 110 also acquires information on the target virtual mobility selected from among multiple virtual mobility options. The mode information acquisition unit 110 transmits the information of the selected control mode to the arbitration unit 140. The mode information acquisition unit 110 also transmits the information of the selected target virtual mobility to the on-demand mode calculation unit 130.

[0056] The normal mode calculation unit 120 calculates the target driving force NF for normal mode (hereinafter referred to as "normal target driving force NF") based on signals from the sensor system 50. The normal target driving force NF is the target driving force required to operate the electric vehicle 100 as a normal BEV.

[0057] For example, the normal mode calculation unit 120 calculates the normal target driving force NF using a map. In this case, the map can be configured to provide the normal target driving force NF using the operating state of the driving control member and the driving state of the electric vehicle 100 as parameters. For example, the map provides the normal target driving force NF using the accelerator opening of the accelerator pedal 22 and the rotational speed of the electric motor 2 as parameters. Furthermore, the map may be configured to provide the normal target driving force NF using the brake opening of the brake pedal 24 and the state of charge (SOC) of the battery 14 as parameters.

[0058] The normal mode calculation unit 120 transmits the calculated normal target driving force NF to the arbitration unit 140. In this embodiment, the processing related to the normal mode calculation unit 120 may be modified as appropriate. The processing related to the normal mode calculation unit 120 can employ known and preferred methods used to calculate the target driving force in conventional BEVs.

[0059] The on-demand mode calculation unit 130 acquires information about the target virtual mobility from the mode information acquisition unit 110. Then, based on the signals from the sensor system 50, the on-demand mode calculation unit 130 calculates the target driving force OF as the on-demand mode (hereinafter referred to as "on-demand target driving force OF"). The on-demand target driving force OF is the target driving force for reproducing the acceleration characteristics of the virtual mobility in the electric vehicle 100 in response to the driver's driving operations. Details of the processing performed by the on-demand mode calculation unit 130 will be described later. The on-demand mode calculation unit 130 transmits the calculated on-demand target driving force OF to the arbitration unit 140.

[0060] The arbitration unit 140 arbitrates the target driving force TF used to control the electric motor 2 according to the selected control mode. Specifically, while the on-demand mode is selected, the arbitration unit 140 transmits the on-demand target driving force OF calculated by the on-demand mode calculation unit 130 to the electric motor control unit 150. Also, while the normal mode is selected, the arbitration unit 140 transmits the normal target driving force NF calculated by the normal mode calculation unit 120 to the electric motor control unit 150. The arbitration unit 140 may gradually change the target driving force TF transmitted to the electric motor control unit 150 when the control mode is switched. For example, when the control mode is switched from the normal mode to the on-demand mode, the arbitration unit 140 may set the target driving force TF to a value that gradually changes from the normal target driving force NF to the on-demand target driving force OF over a certain switching period.

[0061] The drive control device 101a may be configured not to execute processing related to the normal mode calculation unit 120 while the on-demand mode is selected. Similarly, the drive control device 101a may be configured not to execute processing related to the on-demand mode calculation unit 130 while the normal mode is selected. By configuring it in this way, the processing cost of the drive control device 101a in each control mode can be reduced.

[0062] The electric motor control unit 150 controls the electric motor 2 to achieve the target driving force TF transmitted from the arbitration unit 140. More specifically, the electric motor control unit 150 generates a control signal for the inverter 16 according to the target driving force TF. The electric motor control unit 150 then changes the motor torque output by the electric motor 2 via PWM control by the inverter 16.

[0063] In this way, the drive control device 101a calculates the target driving force TF of the electric vehicle 100 according to the control mode and controls the output of the electric motor 2 to achieve the calculated target driving force TF. In particular, according to the drive control device 101a, while the on-demand mode is selected, the output of the electric motor 2 is controlled to reproduce the acceleration characteristics of the target virtual mobility in the electric vehicle 100. On the other hand, while the normal mode is selected, the acceleration characteristics of the electric vehicle 100 are those of a normal BEV.

[0064] Figure 4 shows an example of the acceleration characteristics VC of the target virtual mobility reproduced by the electric vehicle 100. Figure 4 also shows an example of the power characteristics MF of the electric vehicle 100. The power characteristics MF can also be considered as the acceleration characteristics of the electric vehicle 100 when the normal mode is selected.

[0065] While on-demand mode is selected, the acceleration characteristics of the electric vehicle 100 reproduce the acceleration characteristics VC of the target virtual mobility. Therefore, while on-demand mode is selected, the acceleration characteristics of the electric vehicle 100 change to various patterns depending on the target virtual mobility as it is changed. As a result, in on-demand mode, the driver can enjoy the acceleration characteristics of various virtual mobilitys with the electric vehicle 100.

[0066] The following describes in detail the processes performed by the on-demand mode calculation unit 130.

[0067] 4.1 On-Demand Mode Calculation Unit Figure 5 shows an example of the functional configuration of the on-demand mode calculation unit 130. The on-demand mode calculation unit 130 calculates the on-demand target driving force OF. The on-demand mode calculation unit 130 includes a virtual driving environment calculation unit 131 and an on-demand target driving force calculation unit 132 as functional blocks. The on-demand mode calculation unit 130 is also configured to be able to access the on-demand model database D10.

[0068] The on-demand model database D10 is a database that manages multiple on-demand models 200, each modeling multiple virtual mobility devices. The on-demand model database D10 may be stored as data 105 in the storage device 103. Each on-demand model 200 managed by the on-demand model database D10 may be updated as needed. New on-demand models 200 may also be downloaded to the on-demand model database D10 as needed. In the example shown in Figure 5, the on-demand model database D10 manages three on-demand models 200-A, 200-B, and 200-C. Each on-demand model 200 is a model that simulates the driving environment of a virtual mobility device in response to a driver's driving operation, taking the operating state of the driving control components and the driving state of the electric vehicle 100 as input. In particular, each on-demand model 200 is configured to simulate the acceleration characteristics of the virtual mobility device. That is, each on-demand model 200 is configured to simulate at least the driving force applied to the virtual mobility device in response to the driver's driving operation, and the acceleration and deceleration operation of the virtual mobility device due to the action of that driving force. The simulation results of the acceleration and deceleration of virtual mobility using each on-demand model 200 include the virtual acceleration VA of the virtual mobility.

[0069] Typically, each on-demand model 200 includes a control model that simulates the control system associated with the powertrain of the virtual mobility, and a plant model that simulates the acceleration and deceleration of the virtual mobility in response to control signals from the control model. In this case, the plant model includes a powertrain model that operates based on control signals from the control model, and a model for simulating the operation of the virtual mobility due to the action of the virtual driving force of the powertrain model. An example of the configuration of an on-demand model 200 will be described later.

[0070] Each on-demand model 200 also has parameters 201 related to the operation of the virtual mobility in the simulation. Examples of parameters 201 include weight, wheel diameter, gear ratio, maximum torque of the drive source, drive torque response, shift schedule, etc. The content of parameters 201 may differ for each on-demand model 200. The on-demand model 200 represents a model of one virtual mobility through a combination of the on-demand model 200 and the settings of the parameters 201. For example, each virtual mobility represents a model of one virtual mobility through a combination of the on-demand model 200 and the settings of the parameters 201, as shown in the table below. As shown in the table below, the same on-demand model 200 may correspond to different virtual mobilitys. This is the case when the powertrain system types are the same and each virtual mobility can be represented by changing the settings of the parameters 201, for example. [Table 1]

[0071] The virtual driving environment calculation unit 131 acquires information on the target virtual mobility from the mode information acquisition unit 110. The virtual driving environment calculation unit 131 refers to the on-demand model database D10 from the acquired information and reads out the on-demand model 200 (target on-demand model) corresponding to the target virtual mobility. Furthermore, the virtual driving environment calculation unit 131 sets the parameters 201 of the read-out on-demand model 200 according to the target virtual mobility. For example, when the target virtual mobility is "Virtual Mobility B1" in the table above, the virtual driving environment calculation unit 131 refers to the on-demand model database D10 and reads out on-demand model 200-B. Then, the virtual driving environment calculation unit 131 sets the parameter 201-B of on-demand model 200-B to the set value B1.

[0072] The virtual driving environment calculation unit 131 uses the read-out target on-demand model to simulate the virtual driving environment of the target virtual mobility in response to the driver's driving operations. More specifically, the virtual driving environment calculation unit 131 receives signals from the sensor system 50 and acquires information on the operating state of the driving control members and the driving state of the electric vehicle 100 to be used as input to the target on-demand model. For example, the virtual driving environment calculation unit 131 acquires the accelerator opening of the accelerator pedal 22 and the vehicle speed of the electric vehicle 100. In addition, depending on the configuration of the target on-demand model, the virtual driving environment calculation unit 131 may acquire information such as the brake opening of the brake pedal 24, upshift signals, downshift signals, the shift position selected by the pseudo-H-type shifter 26, the amount of depression of the pseudo-clutch pedal 27, the steering angle of the steering wheel, the shift selected by the selector, the rotational speed of the electric motor 2, the SOC of the battery 14, and the yaw rate of the electric vehicle 100. The virtual driving environment calculation unit 131 then simulates the virtual driving environment of the target virtual mobility by inputting the acquired information into the target on-demand model. In particular, the virtual driving environment calculation unit 131 calculates the virtual acceleration VA of the target virtual mobility in response to the driver's driving operations through the simulation of the virtual driving environment of the target virtual mobility. The virtual driving environment calculation unit 131 transmits the calculated virtual acceleration VA to the on-demand target driving force calculation unit 132.

[0073] When the on-demand target driving force calculation unit 132 obtains the virtual acceleration VA, it calculates the driving force required to make the acceleration of the electric vehicle 100 the virtual acceleration VA, and uses this as the on-demand target driving force OF. For example, the on-demand target driving force calculation unit 132 converts the virtual acceleration VA to the on-demand target driving force OF using a simplified inverse model of the electric vehicle 100, as shown in the following equation. In the following equation, m is the vehicle weight of the electric vehicle 100, and F is the vehicle weight. load This is the actual driving resistance acting on the electric vehicle 100. The on-demand mode calculation unit 130 outputs the on-demand target driving force OF calculated by the on-demand target driving force calculation unit 132.

number

[0074] As explained above, the on-demand mode calculation unit 130 calculates the virtual acceleration VA of the target virtual mobility in response to the driver's driving operations by simulating the driving environment of the target virtual mobility using the target on-demand model. The on-demand mode calculation unit 130 then calculates the on-demand target driving force OF so that the acceleration of the electric vehicle 100 becomes the calculated virtual acceleration VA. When the electric vehicle 100 is in on-demand mode, the drive control device 101a changes the motor torque output by the electric motor 2 so that the on-demand target driving force OF is applied to the electric vehicle 100.

[0075] Now, let's consider the case where the driver switches between target virtual mobility devices. In this case, depending on the patterns of the virtual mobility device before the switch (hereinafter referred to as "first virtual mobility") and the virtual mobility device after the switch (hereinafter referred to as "second virtual mobility"), the feel of operation may change significantly before and after the switch. In such cases, it becomes difficult for the driver to immediately adapt to the feel of operation of the second virtual mobility device. As a result, the driver may feel stressed or become complacent about safe driving.

[0076] Therefore, this embodiment proposes a method that can reduce the driver's difficulties after switching to a target virtual mobility. Specifically, the on-demand mode calculation unit 130 is configured to calculate the on-demand target driving force OF in "transition mode" when it is determined that there is a significant change in the feel of operation when the target virtual mobility is switched. In transition mode, at least a part of the driving environment characteristics simulated by the target on-demand model is gradually changed to the characteristics of the second virtual mobility. That is, in transition mode, all the driving environment characteristics of the second virtual mobility are not reproduced immediately after the target virtual mobility is switched.

[0077] In this embodiment, to make a decision regarding the transition mode, the virtual operating environment calculation unit 131 executes a transition mode determination process P10. The virtual operating environment calculation unit 131 performs the transition mode determination process P10 to determine whether or not to enter a transition mode and to generate instruction information that defines the characteristics of the target on-demand model during the transition mode. In addition, each on-demand model 200 has a transition mode setting unit 202 that makes settings to change the operating environment characteristics based on the result of the transition mode determination process P10. The transition mode in this embodiment will be described in detail below.

[0078] 4.2 Transition Mode 4.2.1 Overview As described above, in transition mode, at least some of the driving environment characteristics simulated by the target on-demand model are gradually changed to the characteristics of the second virtual mobility. Here, the driving environment characteristics that are changed in transition mode are typically those that have a significant impact on the change in the feel of operation before and after the switch. Some specific examples of the functions of transition mode are shown below.

[0079] The first specific example concerns changing the characteristics of the change in virtual acceleration VA in response to the amount of operation of the accelerator pedal 22 (accelerator opening) (hereinafter referred to as "accelerator sensitivity"). The characteristics of accelerator sensitivity can be characterized by the maximum and minimum values ​​of accelerator sensitivity. When the characteristics of accelerator sensitivity change significantly, the feel of operation also changes significantly. For example, if the maximum value of accelerator sensitivity of the second virtual vehicle increases significantly compared to the first virtual vehicle, after the switch, the feeling of acceleration will be considerably stronger for the same amount of operation of the accelerator pedal 22 as before the switch. Conversely, if the minimum value of accelerator sensitivity of the second virtual vehicle decreases significantly compared to the first virtual vehicle, after the switch, the feeling of acceleration will be considerably weaker for the same amount of operation of the accelerator pedal 22 as before the switch. When the characteristics of accelerator sensitivity change significantly in this way, the driver may find it difficult to accelerate the electric vehicle 100 appropriately.

[0080] Therefore, in the transition mode according to the first specific example, at least one of the maximum and minimum values ​​of the accelerator sensitivity is gradually changed from the state of the first virtual mobility to the state of the second virtual mobility. Figure 6 is a diagram showing an example of the function of the transition mode according to the first specific example. Figures (A) and (B) in Figure 6 show the characteristic GC (hereinafter referred to as "operation characteristic GC") of the virtual acceleration VA with respect to the amount of operation (accelerator opening) of the accelerator pedal 22 at a certain vehicle speed. GC-1 is the operation characteristic GC of the first virtual mobility. GC-2 is the operation characteristic GC of the second virtual mobility. GC-t is the operation characteristic GC during the transition mode. Each operation characteristic GC is determined by the configuration and settings of each on-demand model 200. Figure 6 (A) is the case in which the maximum value of the accelerator sensitivity is gradually changed from the state of the first virtual mobility to the state of the second virtual mobility, and (B) is the case in which the minimum value of the accelerator sensitivity is gradually changed from the state of the first virtual mobility to the state of the second virtual mobility.

[0081] First, refer to (A) in Figure 6. In the example shown in (A), the maximum accelerator sensitivity of the first virtual mobility is the accelerator sensitivity from when the virtual acceleration VA value goes from G2 to G3. On the other hand, the maximum accelerator sensitivity of the second virtual mobility is the accelerator sensitivity from when the virtual acceleration VA value goes from G1 to G5. Hereafter, we will represent the value of virtual acceleration VA as G and the value of accelerator opening as s, and define accelerator sensitivity as dG / ds. In particular, the accelerator sensitivity of the first virtual mobility is dG F / ds, the accelerator sensitivity of the second virtual mobility is set to dG S / ds, accelerator sensitivity during transition mode is set to dG T Represented as / ds.

[0082] In the example shown in (A), the maximum value of the accelerator sensitivity of the second virtual mobility is max(dG S / ds) is the maximum value of the accelerator sensitivity of the first virtual mobility, max(dG) F It can be seen that it has increased significantly relative to the maximum value of accelerator sensitivity max(dG). Therefore, in the transition mode, the operating characteristic GC-t is set to the maximum value of accelerator sensitivity max(dG). T / ds) is max(dGF from max(dG S / ds) changes step by step to max(dG T / ds). This can also be said to limit max(dG F / ds) with max(dG / ds). In the operation characteristic GC-t during the transition mode, the change point of the acceleration sensitivity according to the value of the virtual acceleration VA is equivalent to the operation characteristic GC-2 of the second virtual mobility. In the example shown in (A), both the operation characteristic GC-t and the operation characteristic GC-2 change the acceleration sensitivity when the value of the virtual acceleration VA becomes G1, G5, and G6. Thereby, the operation characteristic GC-t during the transition mode can suppress a large change in the operation feeling while reproducing the operation characteristic GC-2 of the second virtual mobility.

[0083] max(dG S / ds) is max(dG F / ds) with respect to whether max(dG S / ds) is max(dG F / ds) increases significantly can be determined by whether max(dG F / ds) is greater than a threshold value related to max(dG S / ds) (hereinafter referred to as the "first threshold value"). More specifically, when the following formula is satisfied, max(dG S / ds) can be determined to increase significantly with respect to max(dG F / ds). In the following formula, the first threshold value is max(dG F / ds) × α. Here, α is set to a value of 1 or more, and is a measure indicating how much max(dG S / ds) is greater than max(dG F / ds). Typically, α is set to a value from 1.0 to 2.0. However, α may be experimentally and preferably determined according to the environment to which the present embodiment is applied.

Equation

[0084] Next, refer to (B) in FIG. 6. In the example shown in (B), the minimum value min(dG F / ds) is the accelerator sensitivity until the virtual acceleration VA becomes G8. On the other hand, the minimum value of the accelerator sensitivity of the second virtual mobility is min(dG S (ds) is the accelerator sensitivity until the virtual acceleration VA becomes G7. In the example shown in (B), min(dG S / ds) is min(dG F It can be seen that it has decreased significantly relative to the minimum value of accelerator sensitivity min(dG). Therefore, in the transition mode, the operating characteristic GC-t is set to the minimum value of accelerator sensitivity min(dG). T / ds) is min(dG F / ds) to min(dG S It changes in steps to min(dG). T / ds) min(dG F You can also restrict it using / ds.

[0085] min(dG S / ds) is min(dG F To determine whether it has decreased significantly relative to / ds, use min(dG S / ds) is min(dG F This can be done by determining whether it is smaller than the threshold related to / ds (hereinafter referred to as the "second threshold"). More specifically, when the following equation is satisfied, min(dG S / ds) is min(dG F It can be determined that the value has decreased significantly relative to / ds). In the following formula, the second threshold is min(dG F The formula is ( / ds) × β. Here, β is set to a value less than or equal to 1, and min(dG S / ds) is min(dG F This is a measure that indicates how much smaller it is relative to ( / ds). Typically, β is set to a value between 0 and 1.0. However, β may be experimentally determined to suit the environment in which this embodiment is applied.

number

[0086] In the transition mode described in this first specific example, at least one of the maximum and minimum values ​​of the accelerator sensitivity is gradually changed from the state of the first virtual mobility to the state of the second virtual mobility. Here, the timing of gradually changing at least one of the maximum and minimum values ​​of the accelerator sensitivity can be determined from various perspectives as shown below.

[0087] The first perspective is the operating time from the start of the transition mode. According to this perspective, as the operating time increases, max(dG T / ds) is max(dG F / ds) to max(dG S It changes in steps to / ds), or / furthermore, min(dG T / ds) is min(dG F / ds) to min(dG S It changes gradually to / ds).

[0088] The second perspective is the distance traveled since the start of the transition mode. According to this perspective, as the distance traveled increases, max(dG T / ds) is max(dG F / ds) to max(dG S It changes in steps to / ds), or / furthermore, min(dG T / ds) is min(dG F / ds) to min(dG S It changes gradually to / ds).

[0089] The third perspective is the driver's level of adaptation to the feel of the controls. According to this perspective, as the level of adaptation increases, max(dG) T / ds) is max(dG F / ds) to max(dG S It changes in steps to / ds), or / furthermore, min(dG T / ds) is min(dG F / ds) to min(dG SThe adaptation level changes in stages (ds). The adaptation level can be determined from the driver's driving operation pattern (accelerator work). For example, if the driver is performing driving operations that smoothly accelerate the electric vehicle 100, it can be determined that the adaptation level is increasing. Conversely, if the driver's driving operations when accelerating the electric vehicle 100 are unstable (for example, repeatedly pressing and releasing the accelerator pedal 22), it can be determined that the adaptation level is not increasing.

[0090] The fourth perspective is the driver's input. According to this perspective, the max(dG) is determined in response to the driver's input. T / ds) is max(dG F / ds) to max(dG S It changes in steps to / ds), or / furthermore, min(dG T / ds) is min(dG F / ds) to min(dG S The value changes in steps (max(dG)). The driver, for example, performs an input operation via the HMI 20 to change at least one of the maximum and minimum values ​​of the accelerator sensitivity in steps. Alternatively, the electric vehicle 100 may be provided with a separate operating member for changing at least one of the maximum and minimum values ​​of the accelerator sensitivity in steps. Also in this view, an input operation to change it in the reverse direction may be possible. For example, max(dG) T / ds) to max(dG F It may be possible to perform an input operation that changes the input to the / ds side.

[0091] As described above, from these viewpoints, the timing for gradually changing at least one of the maximum and minimum values ​​of the accelerator sensitivity can be determined. The above viewpoints can also be combined. The number of change steps may be suitably determined depending on the environment to which this embodiment is applied. In particular, the number of change steps may be one. That is, max(dG) in one step. T / ds) is max(dG F / ds) to max(dG S / ds) changes, or / furthermore, min(dG T / ds) is min(dG F / ds) to min(dG S It may also change to / ds).

[0092] The conditions for initiating the transition mode related to the first specific example (hereinafter referred to as the "transition initiation conditions") are the maximum value of the accelerator opening of the second virtual mobility, max(dG) S The value of / ds) is greater than the first threshold, or the minimum value of the accelerator opening of the second virtual mobility min(dG) S The condition is that max(dG) is less than the second threshold. Furthermore, the transition mode according to the first specific example can be realized, for example, by appropriately changing the settings of the control map that defines the target value of the virtual driving force of the target virtual mobility for a given combination of accelerator opening and vehicle speed in the target on-demand model. Accordingly, according to the first specific example, in the transition mode determination process P10, the virtual driving environment calculation unit 131 determines max(dG) S Whether / ds) is greater than the first threshold, and min(dG S It determines whether the maximum accelerator opening value (max(dG)) is less than the second threshold. When the transition start conditions for the first specific example are met, the virtual driving environment calculation unit 131 notifies the target on-demand model to enter transition mode, and determines the maximum accelerator opening value (max(dG)) during transition mode. T / ds) or minimum value min(dG) T The instruction information is generated as / ds). The transition mode setting unit 202 of the target on-demand model, upon receiving the instruction to enter transition mode, changes the control map settings according to the instruction information.

[0093] Next, let's discuss a second specific example. This second example concerns a case where the required driving operations are changed. When a driving operation component with a characteristic function is added to the set of driving operation components used in driving operations (hereinafter also simply referred to as the "set of driving operation components"), the feel of operation changes significantly. For example, consider a case where the first virtual mobility is a vehicle equipped with an automatic transmission (AT) and the second virtual mobility is a vehicle equipped with a manual transmission (MT). In this case, the set of driving operation components for the second virtual mobility includes a pseudo-H-type shifter 26 and a pseudo-clutch pedal 27 in addition to the set of driving operation components for the first virtual mobility. Since the operation of the pseudo-H-type shifter 26 and the pseudo-clutch pedal 27 is specific to vehicles equipped with an MT, the feel of operation will change significantly between the first and second virtual mobility. As a result, the driver may find driving operations difficult.

[0094] Therefore, in the transition mode relating to the second specific example, the driving operation gradually changes from a state in which the specific operating member of the second virtual mobility is not used to a state in which the characteristic operating member of the second virtual mobility is used. Here, the "specific operating member" is a driving operating member predetermined from a set of driving operating members for each virtual mobility. Typically, the specific operating member is a driving operating member that has a characteristic function in the driving operation of that virtual mobility. For example, when the virtual mobility is a vehicle equipped with a manual transmission, the specific operating member is a pseudo-H type shifter 26 or a pseudo-clutch pedal 27. However, there may be virtual mobilitys for which no specific operating member is defined in the set of driving operating members. The specific operating member for each virtual mobility may be managed by a computer program 104 or data 105.

[0095] Figure 7 shows an example of the function of the transition mode relating to the second specific example. Figures (A) and (B) in Figure 7 show the set of driving control members DS-1 for the first virtual mobility, the set of driving control members DS-2 for the second virtual mobility, and specific operating members within the set of driving control members DS-2, respectively.

[0096] First, refer to (A) in Figure 7. In the example shown in (A), the pseudo-paddle shifter 25, which is a specific operating member in the set of driving operating members DS-2, is not included in the set of driving operating members DS-1. The second virtual mobility in the example shown in (A) is, for example, a vehicle that can be manually shifted in response to the operation of the paddle shifter. Therefore, in the example shown in (A), the driving operation during the transition mode first results in a state where gear changes are performed automatically without using the pseudo-paddle shifter 25. Then, in the next stage, the driving operation results in a state where gear changes are performed in response to the operation of the pseudo-paddle shifter 25.

[0097] Next, refer to (B) in Figure 7. In the example shown in (B), the pseudo-H-type shifter 26 and pseudo-clutch pedal 27, which are specific operating members in the set of driving operating members DS-2, are not included in the set of driving operating members DS-1. The second virtual mobility in the example shown in (B) is, for example, a vehicle equipped with a manual transmission, in which manual shifting is possible by operating the H-type shifter while the clutch pedal is depressed. In the example shown in (B), the driving operation during the transition mode first results in a state where gear changes are performed automatically without using the pseudo-H-type shifter 26 and pseudo-clutch pedal 27. In the next stage, the driving operation results in a state where gear changes are performed only by operating the pseudo-H-type shifter 26. That is, at this stage, it is not necessary to depress the pseudo-clutch pedal 27. Then, in the next stage, the driving operation results in a state where both the pseudo-H-type shifter 26 and the pseudo-clutch pedal 27 need to be operated for gear changes.

[0098] Thus, the transition mode according to the second specific example gradually changes the driving operation from a state in which a specific operating member of the second virtual mobility is not used to a state in which a specific operating member of the second virtual mobility is used. Here, the timing of the gradual change in the state of the driving operation may be the same as in the first specific example. That is, the timing of the gradual change in the state of the driving operation may be determined from the perspective of driving time, driving distance, the driver's level of adaptation to the feel of operation, and the driver's input operations, etc. Furthermore, how the stages of change are set may be suitably determined according to the environment in which this embodiment is applied. For example, in the example shown in (B), the driving operation may be configured such that operation of both the pseudo-H type shifter 26 and the pseudo-clutch pedal 27 is required in one stage.

[0099] The transition initiation condition for the second specific example is that a specific operating component in the set of operating components DS-2 of the second virtual mobility is not included in the set of operating components DS-1 of the first virtual mobility. Furthermore, the transition mode for the second specific example can be realized, for example, by appropriately switching some processing in the control model or plant model in the target on-demand model. Accordingly, according to the second specific example, in the transition mode determination process P10, the virtual operating environment calculation unit 131 determines whether a specific operating component in the set of operating components DS-2 is included in the set of operating components DS-1. When the transition initiation condition for the second specific example is met, the virtual operating environment calculation unit 131 notifies the target on-demand model that it is entering transition mode and generates instruction information for the stages of operation during the transition mode. The transition mode setting unit 202 of the target on-demand model, upon receiving the notification that it is entering transition mode, switches some processing in the control model or plant model according to the instruction information.

[0100] The above describes specific examples of the functions of the transition mode. The first and second examples described above can be combined. Furthermore, the transition mode can employ different configurations from the above examples, as long as at least a part of the driving environment characteristics simulated by the target on-demand model gradually changes to the characteristics of the second virtual mobility. For example, this could involve gradually changing the maximum value of the virtual acceleration VA from the state of the first virtual mobility to the state of the second virtual mobility.

[0101] Furthermore, in transition mode, the drive control device 101a may be configured to provide prior notification to the driver before changing the driving environment characteristics by one step. For example, the drive control device 101a may display a prior notification pop-up on the display. In particular, in the prior notification, the drive control device 101a may ask for the driver's consent to change the driving environment characteristics. Then, on the condition that the driver consents, the on-demand mode calculation unit 130 may be configured to change the driving environment characteristics by one step. Alternatively, in transition mode, the drive control device 101a may be configured to provide post-notification to the driver after changing the driving environment characteristics by one step. In particular, in the post-notification, the drive control device 101a may ask for the driver's agreement to the change in driving environment characteristics. Then, if the driver does not agree, the on-demand mode calculation unit 130 may be configured to revert the driving environment characteristics by one step. By adopting such a configuration, it becomes possible to change the driving environment characteristics in stages while taking the driver's intentions into consideration.

[0102] As explained above, the transition mode makes it possible to suppress significant changes in the feel of operation after switching the target virtual mobility. As a result, the driver's difficulties after switching the target virtual mobility can be reduced. In particular, in the transition mode, after the target virtual mobility is switched, at least a part of the driving environment characteristics simulated by the target on-demand model can first take into account the characteristics of the first virtual mobility. This makes it possible to further enhance the effect.

[0103] 4.2.2 Processing Flow Figure 8 is a flowchart showing the processing flow of the virtual operating environment calculation unit 131 in the transition mode determination process P10. The processing flow shown in Figure 8 may be executed repeatedly at a predetermined processing cycle.

[0104] First, in step S100, the virtual driving environment calculation unit 131 determines whether or not the target virtual mobility has been switched. The virtual driving environment calculation unit 131 can determine whether or not the target virtual mobility has been switched from the information of the target virtual mobility obtained from the mode information acquisition unit 110. If the target virtual mobility has not been switched (step S100; No), the virtual driving environment calculation unit 131 terminates the current process without making any decisions regarding the transition mode. If the target virtual mobility has been switched (step S100; Yes), the process proceeds to step S200.

[0105] In step S200, the virtual driving environment calculation unit 131 acquires the changes in the driving environment characteristics of the second virtual mobility relative to the first virtual mobility. For example, the virtual driving environment calculation unit 131 acquires that the changes include the accelerator sensitivity characteristics, the set of driving operation members, the acceleration characteristics VC, etc. The virtual driving environment calculation unit 131 can acquire the changes in the driving environment characteristics of the second virtual mobility relative to the first virtual mobility by referring to the driving environment characteristics of each virtual mobility that are managed in advance as a computer program 104 or data 105, for example.

[0106] After step S200, in step S300, the virtual operating environment calculation unit 131 determines whether the changes in the operating environment characteristics satisfy the transition start conditions. The determination of whether the transition start conditions are satisfied may be made for each change in the operating environment characteristics. Figure 9 is a flowchart showing an example of the process related to step S300.

[0107] Figure 9(A) shows an example of processing when the accelerator sensitivity characteristics are changed. In step S311, the virtual driving environment calculation unit 131 calculates the maximum value max(dG) of the accelerator sensitivity of the second virtual mobility. S / ds) is the first threshold (max(dG F Determine whether it is greater than (ds) × α). max(dG S When max(dG) is greater than the first threshold (step S311; Yes), the virtual driving environment calculation unit 131 determines that the transition start condition is met with respect to the accelerator sensitivity characteristics (step S331). On the other hand, max(dG) S When / ds) is less than or equal to the first threshold (step S311; No), the virtual driving environment calculation unit 131 then calculates the minimum value of the accelerator sensitivity of the second virtual mobility min(dG S / ds) is the second threshold (min(dG) F Determine whether it is smaller than ( / ds) × β) (Step S321). min(dG S When min(dG) is less than the second threshold (step S321; Yes), the virtual driving environment calculation unit 131 determines that the transition start condition is met with respect to the accelerator sensitivity characteristics (step S331). S When / ds) is equal to or greater than the second threshold (step S321; No), the virtual driving environment calculation unit 131 determines that the transition start condition with respect to the accelerator sensitivity characteristics is not met and terminates the process.

[0108] Figure 9(B) shows an example of the process when the set of driving control components is the point of change. In step S312, the virtual driving environment calculation unit 131 determines whether the set of driving control components of the first virtual mobility includes a specific control component of the second virtual mobility. If the set of driving control components of the first virtual mobility includes a specific control component of the second virtual mobility (step S312; Yes), the virtual driving environment calculation unit 131 terminates the process, determining that the transition start condition is not met with respect to the set of driving control components. If the set of driving control components of the first virtual mobility does not include a specific control component of the second virtual mobility (step S312; No), the virtual driving environment calculation unit 131 determines that the transition start condition is met with respect to the set of driving control components (step S322).

[0109] Refer to Figure 8 again. If it is determined in step S300 that the transition start condition is not met (step S300; No), the virtual driving environment calculation unit 131 skips the transition mode (step S602). In this case, the target on-demand model immediately reproduces the driving environment characteristics of the second virtual mobility after the target virtual mobility is switched. The transition start condition is not met when there is not a significant change in the feel of operation between the first virtual mobility and the second virtual mobility. Therefore, in such cases, by immediately reproducing the driving environment characteristics of the second virtual mobility, the driver can immediately enjoy the feel of operation of the second virtual mobility.

[0110] If it is determined in step S300 that the transition start condition is met (step S300; Yes), the virtual driving environment calculation unit 131 starts the transition mode and performs control (step S400). That is, the drive control device 101a controls the output of the electric motor 2 in the transition mode. The driving environment characteristics that are changed in stages during the control of the transition mode may be the changes that were determined to satisfy the transition start condition in step S300. For example, when the transition start condition is met with respect to the accelerator sensitivity characteristics, in the transition mode, at least one of the maximum and minimum values ​​of the accelerator sensitivity is changed in stages from the state of the first virtual mobility to the state of the second virtual mobility (see Figure 6). Also, for example, when the transition start condition is met with respect to the set of driving operation members, the driving operation is changed from a state in which a specific operating member of the second virtual mobility is not used to a state in which a specific operating member of the second virtual mobility is used (see Figure 7).

[0111] After step S400, while in control in transition mode, the virtual driving environment calculation unit 131 determines whether the transition termination conditions are met. The transition termination conditions are conditions that indicate the driver has adapted to the feel of operating the second virtual mobility. The transition termination conditions may include various conditions. The virtual driving environment calculation unit 131 determines whether the transition termination conditions are met based on any of the conditions. Figure 10 is a flowchart showing an example of the process related to step S500.

[0112] Figure 10(A) shows an example of the process in which, in transition mode, as the driving time (or distance traveled) from the start of the transition mode increases, a portion of the driving environment characteristics simulated by the target on-demand model is gradually changed to the characteristics of the second virtual mobility. In step S511, the virtual driving environment calculation unit 131 determines whether the driving time (or distance traveled) from the start of the transition mode exceeds a predetermined value. The predetermined value is, for example, the value obtained by adding a predetermined margin to the value at which the driving environment characteristics simulated by the target on-demand model change to the characteristics of the second virtual mobility. When the driving time (or distance traveled) exceeds the predetermined value, the driving environment characteristics of the target on-demand model have sufficiently changed to the characteristics of the second virtual mobility, and it is considered that the driver has adapted to the feel of operating the second virtual mobility. Therefore, when the driving time (or distance traveled) from the start of the transition mode exceeds the predetermined value (step S511; Yes), the virtual driving environment calculation unit 131 determines that the termination condition is met (step S521). On the other hand, if the operating time (or distance traveled) from the start of the transition mode falls below a predetermined value (step S511; No), the virtual operating environment calculation unit 131 terminates the process, determining that the transition termination condition is not met.

[0113] Figure 10(B) shows an example of the process for determining the end of the transition mode in response to input operations by the driver. The processing flow shown in (B) is executed at predetermined timings during the transition mode. The predetermined timing is, for example, when the driving environment characteristics of the target on-demand model change to match the characteristics of the second virtual mobility. Alternatively, the predetermined timing may be when the transition mode is started. In step S512, the virtual driving environment calculation unit 131 requests input from the driver via the HMI 20 regarding whether they have become accustomed to the feel of operating the second virtual mobility. For example, the virtual driving environment calculation unit 131 displays a window on the display asking the driver to select "Yes" when they determine that they have become accustomed to the feel of operating the second virtual mobility. The virtual driving environment calculation unit 131 may continue to display this window while the transition mode is ongoing. Alternatively, when the window is cleared, the virtual driving environment calculation unit 131 may display the window on the display at regular intervals. When the driver provides input indicating that they have become accustomed to the feel of operating the second virtual mobility device (step S522; Yes), the virtual driving environment calculation unit 131 determines that the termination condition has been met (step S532). On the other hand, when the driver does not provide input indicating that they have become accustomed to the feel of operating the second virtual mobility device (step S522; No), the virtual driving environment calculation unit 131 terminates the process, determining that the transition termination condition has not been met.

[0114] Other conditions for completing the transition include when the driver's level of adaptation to the operating feel reaches a predetermined value or higher, or when a certain amount of time has elapsed or a certain distance has been traveled since the driving environment characteristics of the target on-demand model changed to those of the second virtual mobility.

[0115] Refer to Figure 8 again. If it is determined in step S500 that the transition termination condition is not met (step S500; No), the virtual operating environment calculation unit 131 continues to control the transition mode (step S400). On the other hand, if it is determined in step S500 that the transition termination condition is met (step S500; Yes), the virtual operating environment calculation unit 131 terminates the transition mode.

[0116] As described above, the virtual driving environment calculation unit 131 executes the transition mode determination process P10. Figure 11 shows an example of the transition mode determination process P10. Figure 11 shows the case where the specific operating member of the second virtual mobility is the pseudo-paddle shifter 25. As shown in Figure 11, whether or not a transition mode is set and the driving environment characteristics to be changed in the transition mode are determined by whether or not the pseudo-paddle shifter 25 (specific operating member) is included in the set of driving operating members of the first virtual mobility, and whether or not the change in the characteristics of the accelerator sensitivity is large or small.

[0117] 4.2.3 Variations The transition mode determination process P10 may be configured not to skip transition modes. That is, the transition mode determination process P10 may be configured to enter transition mode regardless of the transition start conditions when the target virtual mobility is switched. By configuring it in this way, the driver's difficulties after the switch of the target virtual mobility can be similarly reduced. Processing costs can also be reduced.

[0118] 4.3 Example Configuration of an On-Demand Model The following describes an example of the configuration of the on-demand model 200 managed by the on-demand model database D10. Figure 12 shows an example of the configuration of the on-demand model 200. The on-demand model 200 includes a control model 210 and a plant model 220. The control model 210 simulates a control system related to the powertrain of the virtual mobility. The plant model 220 simulates the acceleration and deceleration operation of the virtual mobility in response to control signals from the control model 210. The plant model 220 includes a powertrain model that operates based on control signals from the control model 210, and a model for simulating the operation of the virtual mobility due to the action of the virtual driving force of the powertrain model. The control model 210 can also be said to simulate a control system that calculates the requested output for the powertrain of the virtual mobility. The plant model 220 can also be said to simulate physical constraints on the requested output of the powertrain.

[0119] The specifications of the control model 210 and the plant model 220 may differ depending on the type of powertrain system. For example, the control system, transmission, and drivetrain configuration differ between internal combustion engine vehicles and hybrid vehicles. Therefore, the on-demand model 200 for internal combustion engine vehicles and the on-demand model 200 for hybrid vehicles will have different specifications for both the control model 210 and the plant model 220. The example shown in Figure 12 specifically illustrates a case where the virtual mobility is a vehicle equipped with an automatic transmission and capable of manual shifting via paddle shifters.

[0120] The control model 210 includes a target virtual driving force calculation unit 211 and a requested output calculation unit 212. The target virtual driving force calculation unit 211 calculates the virtual driving force (target virtual driving force) to be requested from the powertrain of the virtual mobility based on the control map M10. The control map M10 assigns the target virtual driving force to a combination of accelerator opening and vehicle speed. The settings of the control map M10 can also be changed by the transition mode setting unit 202. When a transition mode is selected, the transition mode setting unit 202 changes the settings of the control map M10 according to the instruction information obtained from the transition mode determination process P10. This makes it possible to change the operating characteristics GC reproduced by the on-demand model 200. In particular, it is possible to change the characteristics of accelerator sensitivity.

[0121] The request output calculation unit 212 acquires the vehicle speed and the target virtual driving force calculated by the target virtual driving force calculation unit 211. The request output calculation unit 212 also acquires the upshift and downshift signals output by the shift switch 35 provided on the simulated paddle shifter 25. Based on the acquired information, the request output calculation unit 212 calculates the request output for the powertrain. The calculated request output includes the target engine torque of the internal combustion engine and the target gear of the transmission. In the example shown in Figure 12, the processing performed by the request output calculation unit 212 is switchable between processing P20-A and processing P20-B. Processing P20-A is a process for reproducing normal driving operations, and processing P20-B is a process for reproducing driving operations without using the simulated paddle shifter 25. For example, in processing P20-A, the request output calculation unit 212 is configured to calculate the target gear of the transmission according to the upshift and downshift signals. On the other hand, in process P20-B, the request output calculation unit 212 calculates the target gear of the transmission according to a predetermined shift schedule based on the vehicle speed and target virtual driving force, without referring to the upshift and downshift signals. When a transition mode is selected, the transition mode setting unit 202 switches the processing of the request output calculation unit 212 between process P20-A and process P20-B according to the instruction information obtained from the transition mode determination process. This makes it possible to change the driving operation during the transition mode.

[0122] The control model 210 transmits the request output calculated by the request output calculation unit 212 to the plant model 220.

[0123] The plant model 220 comprises an internal combustion engine model 221, a transmission model 222, a drivetrain model 223, and a vehicle / environment model 224. The internal combustion engine model 221, the transmission model 222, and the drivetrain model 223 are models of the powertrain from the power source to the drive wheels. The vehicle / environment model 224 is a model for simulating the operation of virtual mobility due to the action of virtual driving force from the powertrain model.

[0124] The internal combustion engine model 221 is a model of the internal combustion engine of a virtual mobility. The internal combustion engine model 221 simulates, for example, the operation of an internal combustion engine in response to a target engine torque input. The internal combustion engine model 221 outputs a virtual engine rotational speed VNe and a virtual engine torque VTe. Parameters 201 that can be changed in the internal combustion engine model 221 depending on the target virtual mobility include, for example, the maximum engine torque and engine torque responsiveness.

[0125] The transmission model 222 is a model of the transmission of a virtual mobility. The transmission model 222 simulates, for example, the operation of the transmission in response to a target gear input. The transmission model 222 outputs a virtual transmission output torque from the gear ratio determined by the virtual engine torque VTe output by the internal combustion engine model 221 and the virtual gear stage. The transmission model 222 includes a stepped transmission model that simulates a stepped transmission and a continuously variable transmission model that simulates a continuously variable transmission. Either the stepped transmission model or the continuously variable transmission model is selected depending on the target virtual mobility. Parameters 201 that can be changed in the transmission model 222 depending on the target virtual mobility include, for example, the gear ratio and the shift schedule. In the case of the stepped transmission model, the gear ratio refers to the gear ratio of each gear stage.

[0126] The drivetrain model 223 is a model of the drivetrain of a virtual mobility. The drivetrain model 223 models, for example, the mechanical structure from the transmission to the drive wheels. The drivetrain model 223 calculates the drive wheel torque using the virtual transmission output torque output by the transmission model 222 and a predetermined reduction ratio, and outputs the virtual driving force of the virtual mobility. Parameters 201 that can be changed in the drivetrain model 223 depending on the target virtual mobility include, for example, the reduction ratio and the maximum allowable torque of the propeller shaft.

[0127] The vehicle / environment model 224 is a model that represents the mechanical characteristics and driving environment of the virtual mobility. The vehicle / environment model 224 calculates the driving resistance acting on the virtual mobility from the driving environment. Then, the vehicle / environment model 224 simulates the acceleration and deceleration of the virtual mobility from the virtual driving force output from the drivetrain model 223, the calculated driving resistance, and the mechanical characteristics of the virtual mobility. The vehicle / environment model 224 outputs a virtual acceleration VA from the acceleration and deceleration of the virtual mobility. Parameters 201 that can be changed in the vehicle / environment model 224 depending on the target virtual mobility include, for example, weight, wheel diameter, and CD value.

[0128] As explained above, an on-demand model 200 can be configured. The on-demand model 200 shown in Figure 12 is an example. The on-demand model 200 can also be configured in more detail depending on the event to be emphasized. For example, consider the case where you want to emphasize the shock or response associated with the gear and clutch engagement of the transmission during kickdown. In this case, the transmission model 222 may be configured to reproduce in detail the gear mechanism of the transmission, such as the planetary ravinio, the inertia of each component, and the change in the transmission path when the clutch is engaged and disengaged. On the other hand, if you want to reduce the computational load of the on-demand model 200, the transmission model 222 may be simply configured to reproduce only the gear ratio.

[0129] 5. In-vehicle equipment control system The control device 101 according to this embodiment functions as an in-vehicle equipment control device that controls the speaker 11 and the instrument 13. More specifically, the processor 102 functions as an in-vehicle equipment control device by executing a computer program 104 for in-vehicle equipment control stored in the storage device 103. In particular, when the electric vehicle 100 is in on-demand mode, the in-vehicle equipment control device controls the speaker 11 and the instrument 13 according to the driving environment of the target virtual mobility. The control of the electric vehicle 100 by the in-vehicle equipment control device when the electric vehicle 100 is in on-demand mode will be described below.

[0130] Figure 13 shows an example of the functional configuration of the in-vehicle equipment control device 101b. When the electric vehicle 100 is in on-demand mode, the in-vehicle equipment control device 101b controls the speaker 11 and instrument 13 according to the driving environment of the target virtual mobility.

[0131] The in-vehicle equipment control device 101b receives signals from the HMI 20 and the sensor system 50. The signals input from the HMI 20 to the in-vehicle equipment control device 101b include a signal indicating the control mode selected by the driver and a signal indicating the target virtual mobility selected by the driver. The signals input from the sensor system 50 to the in-vehicle equipment control device 101b include a signal indicating the vehicle speed of the electric vehicle 100, a signal indicating the operating state of the accelerator pedal 22, a signal indicating the operating state of the brake pedal 24, a signal indicating the rotational speed of the electric motor 2, and a signal indicating the charge state (SOC) of the battery 14.

[0132] The in-vehicle equipment control device 101b includes, as functional blocks, a mode information acquisition unit 110, a virtual driving environment calculation unit 131, a virtual sound generation unit 170, a speaker control unit 180, and an instrument control unit 190. These functional blocks are realized through the cooperation of a processor 102 that executes a computer program 104 and a storage device 103. The mode information acquisition unit 110 may be the same as the one described in Figure 3. The virtual driving environment calculation unit 131 may be the same as the one described in Figure 5.

[0133] The virtual sound generation unit 170 generates virtual sounds that should be heard by the driver in the target virtual mobility in response to the driver's driving operations. The virtual sound is, for example, the engine sound (simulated engine sound) generated by the internal combustion engine of the target virtual mobility when the target virtual mobility is a vehicle equipped with an internal combustion engine (engine vehicle). Alternatively, the virtual sound may be the sound of the drive system of the target virtual mobility. The virtual sound generation unit 170 obtains the sound source of the virtual sound related to the target virtual mobility by referring to the storage device 103. The storage device 103 may store the sound source of the virtual sound related to each target virtual mobility. The virtual sound generation unit 170 also obtains the information necessary to generate the virtual sound from the virtual driving environment calculation unit 131. For example, when the virtual sound is a simulated engine sound, the virtual sound generation unit 170 obtains the virtual engine rotational speed VNe and the virtual engine torque VTe from the virtual driving environment calculation unit 131. The virtual sound generation unit 170 then generates the virtual sound based on the sound source and the information obtained from the virtual driving environment calculation unit 131.

[0134] The virtual sound generation unit 170 executes a process 171 to calculate the sound pressure of the virtual sound and a process 172 to calculate the frequency of the virtual sound. For example, when the virtual sound is a simulated engine sound, in process 171, the sound pressure of the simulated engine sound is calculated from the virtual engine torque VTe using a sound pressure map. The sound pressure map is typically created so that the sound pressure increases as the virtual engine torque VTe increases. In process 172, the frequency of the virtual sound is calculated from the virtual engine rotational speed VNe using a frequency map. The frequency map is typically created so that the frequency increases as the virtual engine rotational speed VNe increases. The virtual sound generation unit 170 transmits the generated virtual sound data to the speaker control unit 180.

[0135] The speaker control unit 180 controls the output of the speaker 11 based on the sound data transmitted from the virtual sound generation unit 170. As a result, a virtual sound is output from the speaker 11.

[0136] The instrument control unit 190 controls the instrument 13 to display information that should be displayed to the driver in the target virtual mobility in response to the driver's driving operations (hereinafter referred to as "virtual display information"). The virtual display information is, for example, information such as the virtual engine speed VNe and virtual gear stage of the target virtual mobility when the target virtual mobility is an engine vehicle. The instrument control unit 190 obtains information related to the virtual display information from the virtual driving environment calculation unit 131. For example, when the target virtual mobility is an engine vehicle, the instrument control unit 190 obtains the virtual engine speed VNe and virtual gear stage from the virtual driving environment calculation unit 131. Then, the instrument control unit 190 controls the display of the instrument 13 based on the obtained information. As a result, the virtual display information is displayed on the instrument 13.

[0137] Thus, according to the in-vehicle equipment control device 101b, when the electric vehicle 100 is in on-demand mode, a virtual sound is output from the speaker 11 and virtual display information is shown on the instrument panel 13. This further enhances the driver's sense of realism, making them feel as if they are driving the target virtual mobility device.

[0138] 6. Others The technical features of this embodiment are not limited to BEVs, but are broadly applicable to any electric vehicle that uses an electric motor as a drive source. For example, the technical features of this embodiment are applicable to hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs) that have a mode in which they run solely on the driving force of an electric motor. They are also applicable to fuel cell electric vehicles (FCEVs) that supply electrical energy generated by a fuel cell to an electric motor. [Explanation of symbols]

[0139] 2 Electric motor 100 Electric Vehicles 101 Control device 102 processors 103 Storage device 200 On-Demand Models

Claims

1. An electric vehicle having an electric motor as its driving source, Operating components used for operation, One or more storage devices that manage multiple on-demand models that model multiple virtual mobilitys with different driving environment characteristics in response to the driver's driving operations, One or more processors that control the output of the electric motor, Equipped with, When the electric vehicle is in on-demand mode, the one or more processors The target on-demand model corresponding to the target virtual mobility selected from the aforementioned plurality of virtual mobility devices is obtained from the one or more storage devices. Based on the operating state of the driving control member and the driving state of the electric vehicle, the virtual acceleration of the target virtual mobility in response to the driver's driving operation is calculated using the target on-demand model. The output of the electric motor is controlled so that the acceleration of the electric vehicle becomes the virtual acceleration. When the target virtual mobility is switched from the first virtual mobility to the second virtual mobility, The output of the electric motor is controlled in a transition mode that gradually changes at least a portion of the operating environment characteristics simulated by the target on-demand model to the characteristics of the second virtual mobility. It is configured in such a way Electric vehicle.

2. An electric vehicle according to claim 1, When the electric vehicle is in the on-demand mode, the one or more processors When the target virtual mobility is switched from the first virtual mobility to the second virtual mobility, The changes in the driving environment characteristics of the second virtual mobility compared to the first virtual mobility are obtained, In response to the fact that the changes in the operating environment characteristics satisfy the transition start conditions indicating a significant change in the feel of operation, the output of the electric motor is controlled in the transition mode. If the changes to the operating environment characteristics do not satisfy the transition start conditions, the transition mode is skipped. It is configured in such a way Electric vehicle.

3. An electric vehicle according to claim 2, The aforementioned operating member includes an accelerator operating device, The aforementioned driving environment characteristics include the accelerator sensitivity characteristics, which are the change in the virtual acceleration with respect to the amount of operation of the accelerator control device. The transition initiation condition includes at least one of the following: the maximum value of the accelerator sensitivity of the second virtual mobility is greater than the first threshold, and the minimum value of the accelerator sensitivity of the second virtual mobility is less than the second threshold. Electric vehicle.

4. An electric vehicle according to claim 3, The first threshold value is a value related to the maximum value of the accelerator sensitivity of the first virtual mobility, The second threshold value is a value related to the minimum value of the accelerator sensitivity of the first virtual mobility. Electric vehicle.

5. An electric vehicle according to claim 3, The transition mode includes gradually changing at least one of the maximum and minimum values ​​of the accelerator sensitivity from the state of the first virtual mobility to the state of the second virtual mobility. Electric vehicle.

6. An electric vehicle according to claim 2, The aforementioned operating environment characteristics include the set of operating components used in the operating operation, The transition initiation condition includes the fact that a specific operating member in the set of operating members of the second virtual mobility is not included in the set of operating members of the first virtual mobility. Electric vehicle.

7. An electric vehicle according to claim 6, The transition mode includes gradually changing the operation from a state in which the specific operating member is not used to a state in which the specific operating member is used. Electric vehicle.

8. An electric vehicle according to any one of claims 1 to 7, When the electric vehicle is in the on-demand mode, the one or more processors The transition mode is terminated upon the fulfillment of the transition termination condition, which indicates that the driver has adapted to the feel of operating the second virtual mobility. It is configured in such a way Electric vehicle.

9. An electric vehicle according to claim 8, The transition mode gradually changes at least a portion of the driving environment characteristics simulated by the target on-demand model to the characteristics of the second virtual mobility as the driving time increases from the time the transition mode is started. The transition termination condition includes the operating time being equal to or greater than a predetermined value. Electric vehicle.

10. An electric vehicle according to claim 8, The transition mode gradually changes at least a portion of the driving environment characteristics simulated by the target on-demand model to the characteristics of the second virtual mobility as the distance traveled from the start of the transition mode increases. The transition termination condition includes the mileage exceeding a predetermined value. Electric vehicle.

11. An electric vehicle according to claim 8, When the electric vehicle is in the on-demand mode, the one or more processors During the transition mode, the driver is asked to indicate whether they have become accustomed to the feel of operating the second virtual mobility device. It is configured in such a way, The transition termination condition includes the driver making the input indicating that they have become accustomed to the feel of operating the second virtual mobility. Electric vehicle.

12. A control device for an electric vehicle having an electric motor as a drive source, One or more storage devices that manage multiple on-demand models that model multiple virtual mobilitys with different driving environment characteristics in response to the driver's driving operations, One or more processors that control the output of the electric motor, Equipped with, The aforementioned electric vehicle is equipped with driving control components used for driving, When the electric vehicle is in on-demand mode, the one or more processors The target on-demand model corresponding to the target virtual mobility selected from the aforementioned plurality of virtual mobility devices is obtained from the one or more storage devices. Based on the operating state of the driving control member and the driving state of the electric vehicle, the virtual acceleration of the target virtual mobility in response to the driver's driving operation is calculated using the target on-demand model. The output of the electric motor is controlled so that the acceleration of the electric vehicle becomes the virtual acceleration. When the target virtual mobility is switched from the first virtual mobility to the second virtual mobility, The output of the electric motor is controlled in a transition mode that gradually changes at least a portion of the driving environment characteristics simulated by the target on-demand model from the characteristics of the first virtual mobility to the characteristics of the second virtual mobility. It is configured in such a way Control device.

13. A control device according to claim 12, When the electric vehicle is in the on-demand mode, the one or more processors When the target virtual mobility is switched from the first virtual mobility to the second virtual mobility, The changes in the driving environment characteristics of the second virtual mobility compared to the first virtual mobility are obtained, In response to the fact that the changes in the operating environment characteristics satisfy the transition start conditions indicating a significant change in the feel of operation, the output of the electric motor is controlled in the transition mode. If the changes to the operating environment characteristics do not satisfy the transition start conditions, the transition mode is skipped. It is configured in such a way Control device.

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