Electric vehicles

Abstract

This invention provides a technology that can improve the reproducibility of the acceleration characteristics of virtual mobility in an electric vehicle equipped with a transmission and an on-demand mode that simulates the acceleration characteristics of virtual mobility. [Solution] The electric vehicle is equipped with one or more processors that control the output of the electric motor and the gear position of the transmission. When the electric vehicle is in on-demand mode, one or more processors obtain the maximum target driving force, which is the maximum value of the target driving force that can be taken at the electric vehicle's current speed, and the maximum realizable driving force, which is the maximum value of the driving force that the electric vehicle can output at the electric vehicle's current speed and the current gear position of the transmission. Then, if the maximum target driving force is greater than the maximum realizable driving force, one or more processors shift down the gear position of the transmission to a specified gear position at a specified timing.

Description

Technical Field

[0001] The present disclosure relates to an electric vehicle having an electric motor as a drive source. In particular, it relates to an electric vehicle provided with a transmission that changes the output of the electric motor according to the gear stage and transmits it to the drive wheels.

Background Art

[0002] An electric motor can be controlled to output a desired motor torque by controlling the applied voltage and the field flux. Utilizing this, a technique for reproducing various driving sensations in an electric vehicle by appropriately controlling the electric motor of the electric vehicle has been considered.

[0003] As one of the elements characterizing the driving sensation, there is an acceleration feeling with respect to the driver's driving operation. The acceleration feeling is an important point when the driver enjoys driving. In particular, preferences for the acceleration feeling vary among drivers. Also, the driver may want to enjoy the acceleration feeling of various mobilities according to their mood.

[0004] Therefore, the inventor related to the present disclosure is considering an "on-demand mode" that pseudo-reproduces the acceleration feeling of a plurality of virtual mobilities in one electric vehicle using a plurality of models that model the plurality of virtual mobilities. In the on-demand mode, the control of the electric motor is performed so as to reproduce the acceleration characteristics when a virtual mobility selected from among the plurality of virtual mobilities is driven in the electric vehicle.

[0005] By the way, conventionally, an electric vehicle provided with a transmission has been considered. For example, Patent Document 1 discloses a technique for improving the driving performance by shortening the shift time with respect to an electric vehicle provided with a transmission. By providing a transmission in an electric vehicle, the power performance of the electric vehicle can be improved.

[0006] In addition, there is the following Patent Document 2 as a document showing the technical level of this technical field.

Prior Art Documents

[0007] [Patent Document 1] Japanese Patent Publication No. 2019-178741 [Patent Document 2] Japanese Patent Publication No. 2018-166386 [Overview of the project] [Problems that the invention aims to solve]

[0008] Consider the case where an electric vehicle equipped with a transmission is driven in on-demand mode. In on-demand mode, the electric vehicle is controlled to reproduce the acceleration characteristics of a virtual mobility device in response to the driver's input. On the other hand, the transmission is controlled according to a predetermined shift schedule in the electric vehicle. In particular, the powertrain configurations of electric vehicles and virtual mobility devices are usually different. Therefore, depending on the driver's input, downshifts to gear positions that do not appear in the operation of the virtual mobility device may occur, which has been a problem in that the reproduction of the acceleration characteristics of the virtual mobility device is impaired. For example, this occurs when the electric vehicle is driving steadily at a medium to high speed and the driver kicks down the accelerator pedal to rapidly accelerate the electric vehicle.

[0009] This disclosure has been made in view of the above-mentioned issues. One objective of this disclosure is to provide a technology that can improve the reproducibility of the acceleration characteristics of virtual mobility in electric vehicles equipped with a transmission. [Means for solving the problem]

[0010] One aspect of this disclosure relates to an electric vehicle having an electric motor as a drive source. The electric vehicle comprises a driving control member used for driving, a transmission, one or more memory devices, and one or more processors. The transmission transmits the output of the electric motor to the drive wheels of the electric vehicle, varying it according to the gear position. 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. One or more processors control the output of the electric motor and the gear position of the transmission. When the electric vehicle is in on-demand mode, one or more processors retrieve a target on-demand model corresponding to a target virtual mobility selected from the multiple virtual mobilitys from one or more memory devices, calculate the virtual acceleration of the target virtual mobility in response to the driver's driving operations using the on-demand model based on the operating state of the driving control member and the driving state of the electric vehicle, calculate the target driving force of the electric vehicle to make the acceleration of the electric vehicle a virtual acceleration, and control the output of the electric motor to apply the target driving force to the electric vehicle. Furthermore, when the electric vehicle is in on-demand mode, one or more processors obtain the maximum target driving force, which is the maximum value of the target driving force that can be taken at the electric vehicle's current speed, and the maximum realizable driving force, which is the maximum driving force that the electric vehicle can output at the electric vehicle's current speed and the current gear of the transmission. If the maximum target driving force is greater than the maximum realizable driving force, the transmission gear is shifted down to a specified gear at a specified timing. [Effects of the Invention]

[0011] According to this disclosure, when the maximum target driving force is greater than the maximum realized driving force, the gear of the transmission 18 is shifted down to the specified gear at a specified timing. This makes it possible to suppress gear shifts that do not occur in the operation of the target virtual mobility due to the driver's driving operation. As a result, the reproducibility of the acceleration characteristics of the target virtual mobility can be improved. [Brief explanation of the drawing]

[0012] [Figure 1]It is a diagram showing the configuration of an electric vehicle according to an embodiment. [Figure 2] It 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 an embodiment. [Figure 3] It is a diagram showing an example of the functional configuration of a control device that functions as a drive control device. [Figure 4] It is a diagram showing an example of a shift schedule. [Figure 5] It is a diagram showing an example of the acceleration characteristics of target virtual mobility reproduced by an electric vehicle. [Figure 6] It is a diagram showing an example of the functional configuration of an on-demand mode calculation unit. [Figure 7] It is a diagram showing an example of a case where the reproducibility of the acceleration characteristics of target virtual mobility is impaired. [Figure 8] It is a flowchart showing the processing flow executed by the on-demand target gear stage calculation unit according to an embodiment. [Figure 9] It is a diagram showing an example of an embodiment of a drive control device according to an embodiment. [Figure 10] It is a diagram showing an example of the configuration of an on-demand model. [Figure 11] It is a flowchart showing the processing flow executed by the on-demand target driving force calculation unit according to a modification. [Figure 12] It is a diagram showing an example of the functional configuration of a control device that functions as an in-vehicle device control device.

Mode for Carrying Out the Invention

[0013] [[ID=*41]]Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In each figure, the same or corresponding parts are denoted by the same reference numerals, and the description thereof is simplified or omitted.

[0014] 1 Configuration of the power system of an electric vehicle FIG. 1 is a diagram schematically showing the configuration of an electric vehicle 100 according to an embodiment of the present disclosure. First, the configuration of the power system of the electric vehicle 100 will be described with reference to FIG. 1.

[0015] The electric vehicle 100 includes an electric motor (M) 2 as a driving source for running. 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 a transmission (T / M) 18. A speed reducer may be provided between the output shaft of the electric motor 2 and the transmission 18. The transmission 18 is connected to a differential gear 6 by a propeller shaft 5. The differential gear 6 is connected to left and right drive wheels 8 by left and right drive shafts 7. The drive wheels 8 may be front wheels or rear wheels. With these configurations, the transmission 18 has a function of changing the output of the electric motor 2 according to the gear stage and transmitting it to the drive wheels 8 of the electric vehicle 100. The switching of the gear stage of the transmission 18 is controlled by a control device 101 described later.

[0016] The inverter 16, the electric motor 2, the speed reducer, and the differential gear 6 may be integrally configured as an e-axle. In this case, the electric vehicle 100 does not include the propeller shaft 5, and the e-axle is connected to the drive shaft 7. As another modification, the configuration of the electric vehicle 100 may be four-wheel drive. For example, the electric vehicle 100 may include a transfer connected to the output shaft of the transmission 18, and the transfer may be configured to distribute the output of the transmission 18 to the front wheels and the rear wheels.

[0017] The inverter 16 is connected to a battery (BATT) 14. The inverter 16 is, for example, a voltage-type inverter and controls the motor torque of the electric motor 2 by PWM control. That is, the electric vehicle 100 is a battery electric vehicle (BEV: battery electric vehicle) that runs on electric energy stored in the battery 14 using the electric motor 2 as a driving source.

[0018] 2 Configuration of the control system of the electric vehicle Subsequently, the configuration of the control system of the electric vehicle 100 will be described with reference to FIG. 1.

[0019] 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.

[0020] The electric vehicle 100 is also 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. The electric vehicle 100 may also 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.

[0021] The electric vehicle 100 is also 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.

[0022] The accelerator pedal 22 and the brake pedal 24 are each one of the driving control components used to drive the electric vehicle 100. In addition, the electric vehicle 100 may be equipped with various other driving control components, such as a steering wheel for steering.

[0023] The electric vehicle 100 is also 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.

[0024] The electric vehicle 100 is also 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.

[0025] The electric vehicle 100 is also 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.

[0026] The electric vehicle 100 is also equipped with a speaker 21. The speaker 21 includes at least an in-vehicle speaker that generates sound inside the cabin of the electric vehicle 100. As another example, the speaker 21 may also include an external speaker that generates sound outside the electric vehicle 100. The electric vehicle 100 may be equipped with both an in-vehicle speaker and an external speaker as the speaker 21. The speaker 21 may be configured as part of the HMI 20. The output of the speaker 21 is controlled by the control device 101, which will be described later.

[0027] The electric vehicle 100 is also equipped with an instrument cluster 23. The instrument cluster 23 displays various types of information. Examples of instruments 23 include a speedometer, odometer, tachometer, trip meter, battery level indicator, etc. The instrument cluster 23 may also be configured as part of the HMI 22. The display of the instrument cluster 23 is controlled by the control device 101, which will be described later.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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 as follows.

[0037] 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.

[0038] 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.

[0039] On the other hand, when the option "Target Virtual Mobility" is selected, the options "CONV" and "HEV" are then displayed on the settings menu screen. The options "CONV" and "HEV" represent classifications of multiple virtual mobility options that can be selected in on-demand mode. CONV is a classification that represents conventional vehicles equipped with internal combustion engines. HEV is a classification that represents hybrid electronic vehicles. When the option "CONV" is selected, the options "Virtual Mobility A1", "Virtual Mobility A2", and "Virtual Mobility B1" are then displayed on the settings menu screen. Virtual Mobility A1, Virtual Mobility A2, and Virtual Mobility B1 are virtual mobility options that are classified as CONV among the multiple virtual mobility options that can be selected. Similarly, when the option "HEV" is selected, the options "Virtual Mobility C1" and "Virtual Mobility C2" are then displayed on the settings menu screen. Virtual Mobility C1 and Virtual Mobility C2 are virtual mobility options that are classified as HEV among the multiple virtual mobility options that can be selected. If any of these options is selected, the HMI20 determines that the selected virtual mobility is the target virtual mobility. For example, if the option "Virtual Mobility A2" is selected, the HMI20 determines that Virtual Mobility A2 is the target virtual mobility. In this way, the HMI20 accepts the driver's input for the selection of the target virtual mobility.

[0040] In the above explanation, the classification of multiple virtual mobility options is merely an example, and the options related to classification may be changed as appropriate. For example, the options related to classification may further include options indicating plug-in hybrid electric vehicles (PHEVs) and fuel cell electric vehicles (FCEVs). Alternatively, the options related to classification may indicate other classifications, such as classifications related to the type of power source installed (e.g., inline 4-cylinder turbocharged engine, flat 6-cylinder engine, V12 engine, battery, fuel cell). Or, if the option "On-Demand Mode" is selected, the settings menu screen may display options related to virtual mobility without displaying options related to classification.

[0041] 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.

[0042] 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.

[0043] 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 and the gear stages of the transmission 18 in response to 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.

[0044] 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 and target gear position TG of the electric vehicle 100 in accordance with the driver's driving operations. The drive control device 101a then controls the electric motor 2 and the transmission 18 to achieve the calculated target driving force TF and target gear position TG.

[0045] 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 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.

[0046] 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 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.

[0047] 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, a arbitration unit 140, an electric motor control unit 150, and a transmission control unit 160. These functional blocks are realized through the cooperation of a processor 102 that executes a computer program 104 and a storage device 103.

[0048] 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.

[0049] The normal mode calculation unit 120 calculates the target driving force NF (hereinafter referred to as "normal target driving force NF") and the target gear position NG (hereinafter referred to as "normal target gear position NG") for normal mode based on signals from the sensor system 50. The normal target driving force NF and the normal target gear position NG are the target driving force and target gear position, respectively, for operating the electric vehicle 100 as a normal BEV.

[0050] 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.

[0051] The normal mode calculation unit 120 also calculates the normal target gear NG according to a predetermined shift schedule, for example. The shift schedule is configured to determine the usage range of each gear for the current vehicle speed and target driving force of the electric vehicle 100. The shift schedule may be given by a gear shift diagram. The shift schedule is configured appropriately considering the fuel efficiency and maintenance performance of the electric vehicle 100. The shift schedule may be pre-stored as data 105 in the storage device 103.

[0052] Figure 4 shows an example of a shift schedule. Figure 4 also shows an example of the power characteristic MF, which indicates the driving force (acceleration) that the electric vehicle 100 can output. The power characteristic MF changes according to the gear stage of the transmission 18. Specifically, the larger the gear ratio of the transmission 18, the greater the maximum driving force of the electric vehicle 100. On the other hand, the larger the gear ratio of the transmission 18, the lower the maximum vehicle speed of the electric vehicle 100. Figure 4 shows three power characteristics MF-1 (dashed line), MF-2 (dotted line), and MF-3 (dotted line) for each gear stage when the transmission 18 has three gear stages (1st, 2nd, and 3rd). The gear ratios of the gear stages increase in this order for power characteristics MF-1, MF-2, and MF-3. In other words, output characteristics MF-1, MF-2, and MF-3 are the output characteristics MF when the gear position of the transmission 18 is 1st, 2nd, and 3rd, respectively.

[0053] Furthermore, Figure 4 shows the usable range RU for each gear stage determined by the shift schedule. Usable range RU-1 is the usable range RU for the 1st gear stage. Usable range RU-2 is the usable range RU for the 2nd gear stage. Usable range RU-3 is the usable range RU for the 3rd gear stage. As shown in Figure 4, the gear stage to be used for the current vehicle speed and target driving force of the electric vehicle 100 can be determined from the usable range RU determined by the shift schedule. In particular, the shift timing occurs when crossing the usable range RU. The normal target gear stage calculation unit 123 calculates the gear stage identified from the current vehicle speed and normal target driving force NF of the electric vehicle 100 as the normal target gear stage NG, according to the shift schedule shown in Figure 4.

[0054] Refer to Figure 3 again. The normal mode calculation unit 120 transmits the calculated normal target driving force NF and normal target gear stage NG 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 and target gear stage in conventional BEVs.

[0055] The on-demand mode calculation unit 130 acquires information on 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 (hereinafter referred to as "on-demand target driving force OF") and the target gear stage OG (hereinafter referred to as "on-demand target gear stage OG") as the on-demand mode. 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 and on-demand target gear stage OG to the arbitration unit 140.

[0056] The arbitration unit 140 arbitrates the target driving force TF used for controlling the electric motor 2 and the target gear position TG used for controlling the transmission 18, according to the selected control mode. The arbitration unit 140 executes a process 141 for arbitrating the target driving force TF and a process 142 for arbitrating the target gear position TG.

[0057] In process 141, 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 while the on-demand mode is selected. The arbitration unit 140 also transmits the normal target driving force NF calculated by the normal mode calculation unit 120 to the electric motor control unit 150 while the normal mode is selected. In process 141, 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 normal mode to 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.

[0058] In process 142, while the on-demand mode is selected, the arbitration unit 140 transmits the on-demand target gear position OG calculated by the on-demand mode calculation unit 130 to the transmission control unit 160. Also, while the normal mode is selected, the arbitration unit 140 transmits the normal target gear position NG calculated by the normal mode calculation unit 120 to the transmission control unit 160.

[0059] 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 load of the drive control device 101a in each control mode can be reduced.

[0060] 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.

[0061] The transmission control unit 160 controls the transmission 18 to achieve the target gear position TG transmitted from the arbitration unit 140. More specifically, the transmission control unit 160 generates a control signal for the transmission 18 according to the target gear position TG. The transmission 18 changes the gear position according to the control signal from the transmission control unit 160.

[0062] In this way, the drive control device 101a calculates the target driving force TF and target gear position TG of the electric vehicle 100 according to the control mode, and controls the electric motor 2 and transmission 18 to achieve the calculated target driving force TF and target gear position TG. In particular, according to the drive control device 101a, while the on-demand mode is selected, 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.

[0063] Figure 5 shows an example of the acceleration characteristics VC of the target virtual mobility reproduced by the electric vehicle 100. Figure 5 also shows, for comparison, an example of the output characteristics MF of the electric vehicle 100 when the transmission 18 has three gear stages (1st, 2nd, and 3rd), similar to the case shown in Figure 4. Each output characteristic MF can also be considered as the acceleration characteristics of the electric vehicle 100 when the normal mode is selected.

[0064] 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 sensation of various virtual mobilitys with the electric vehicle 100.

[0065] The following describes in detail the processes performed by the on-demand mode calculation unit 130.

[0066] 4.1 On-Demand Mode Calculation Unit Figure 6 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 and the on-demand target gear stage OG. The on-demand mode calculation unit 130 includes, as functional blocks, a virtual driving environment calculation unit 131, an on-demand target driving force calculation unit 132, and an on-demand target gear stage calculation unit 133. The on-demand mode calculation unit 130 is also configured to access the on-demand model database D10.

[0067] 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 in the storage device 103 as data 105. 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 6, 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.

[0068] 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.

[0069] 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]

[0070] 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.

[0071] 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 input to the target on-demand model. For example, the virtual driving environment calculation unit 131 acquires the accelerator opening degree of the accelerator pedal 22 and the vehicle speed of the electric vehicle 100. Depending on the configuration of the target on-demand model, the virtual driving environment calculation unit 131 may also acquire information such as the accelerator opening speed of the accelerator pedal 22, the brake opening degree and brake opening speed of the brake pedal 24, the steering angle of the steering wheel, and the yaw rate of the electric vehicle 100. The virtual driving environment calculation unit 131 then inputs the acquired information into the target on-demand model to simulate the virtual driving environment of the target virtual mobility. 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 by simulating 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.

[0072] In this embodiment, the virtual driving environment calculation unit 131 further acquires the maximum value TFm of the on-demand target driving force OF that can be taken at the current vehicle speed of the electric vehicle 100 (hereinafter referred to as "maximum target driving force TFm"). The maximum target driving force TFm can be obtained from the acceleration characteristics VC of the target virtual mobility. For example, Figure 5 shows the maximum target driving force TFm at the current vehicle speed Va of the electric vehicle 100 with respect to the acceleration characteristics VC of the target virtual mobility. The acceleration characteristics VC of the target virtual mobility is determined by the target on-demand model. Therefore, once the target virtual mobility is determined, the virtual driving environment calculation unit 131 can determine its acceleration characteristics VC. The virtual driving environment calculation unit 131 may manage the acceleration characteristics VC of each virtual mobility in advance. Alternatively, each on-demand model 200 may be configured to output acceleration characteristics VC. The virtual driving environment calculation unit 131 acquires the maximum target driving force TFm from the current vehicle speed Va of the electric vehicle 100 and the determined acceleration characteristics VC of the target virtual mobility. The virtual driving environment calculation unit 131 transmits the acquired maximum target driving force TFm to the on-demand target gear stage calculation unit 133.

[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] The on-demand target gear stage calculation unit 133 acquires various signals from the sensor system 50. The on-demand target gear stage calculation unit 133 also acquires the maximum target driving force TFm from the virtual driving environment calculation unit 131. The on-demand target gear stage calculation unit 133 also acquires the on-demand target driving force OF calculated by the on-demand target driving force calculation unit 132. Then, the on-demand target gear stage calculation unit 133 calculates the on-demand target gear stage OG from the acquired information. The on-demand mode calculation unit 130 outputs the on-demand target gear stage OG calculated by the on-demand target gear stage calculation unit 133.

[0075] Here, we consider the case where the on-demand target gear calculation unit 133 calculates the on-demand target gear OG according to a predetermined shift schedule, similar to the normal mode. In this case, depending on the driver's operation, a gear downshift that does not occur in the operation of the target virtual mobility may occur. This is because the powertrain configurations of the electric vehicle 100 and the target virtual mobility are usually different. In particular, the presence or absence of a transmission, the number of gears, and the gear ratios may differ between the electric vehicle 100 and the target virtual mobility. If a gear downshift that does not occur in the operation of the target virtual mobility occurs, the reproducibility of the acceleration characteristics VC of the target virtual mobility may be impaired as a result.

[0076] Figure 7 shows an example of a case where the reproducibility of the acceleration characteristics VC of the target virtual mobility is impaired due to a gear shift down. Figure 7 shows the accelerator opening, on-demand target driving force OF (dotted line), the driving force of the electric vehicle 100 (solid line), and the change in gear over time. In the example shown in Figure 7, the driver performs a kickdown at time t0. As a result, the on-demand target driving force OF increases significantly from time t1. Along with this increase in the on-demand target driving force OF, a gear shift down from 3rd to 2nd occurs at time t1. Here, RF-2 shown in Figure 7 is the maximum value RF (hereinafter referred to as "maximum realized driving force RF") of the driving force that can be output at the current vehicle speed Va of the electric vehicle 100 when the current gear of the transmission 18 is 2nd. RF-3 is the maximum realized driving force RF-3 when the current gear of the transmission 18 is 3rd. In other words, the downshift at time t1 occurred because the on-demand target driving force OF, which had increased since time t1, exceeded the maximum realized driving force RF-3. As a result of this downshift, the driving force (acceleration) of the electric vehicle 100 stagnated, and a discrepancy occurred between the driving force of the electric vehicle 100 and the on-demand target driving force OF between time t1 and time t2. In other words, a discrepancy occurred between the acceleration of the electric vehicle 100 and the virtual acceleration VA. When a downshift of a gear position that does not appear in the operation of the target virtual mobility occurs in this way, the reproducibility of the acceleration characteristics VC of the target virtual mobility may be impaired.

[0077] Therefore, the on-demand target gear stage calculation unit 133 according to this embodiment performs processing to address the above-mentioned problems and calculates the on-demand target gear stage OG. More specifically, when the maximum target driving force TFm is greater than the maximum realized driving force RF, the on-demand target gear stage OG is calculated so as to shift down the gear stage of the transmission 18 at a specified timing. The processing performed by the on-demand target gear stage calculation unit 133 is described in detail below.

[0078] 4.2 Processing of the On-Demand Target Gear Stage Calculation Unit Figure 8 is a flowchart showing the processing flow of the on-demand target gear stage calculation unit 133 (more specifically, the processor 102). The processing flow shown in Figure 8 is executed repeatedly at a predetermined processing cycle.

[0079] In step S510, the on-demand target gear stage calculation unit 133 acquires various information. At a minimum, the on-demand target gear stage calculation unit 133 acquires information on the current vehicle speed Va of the electric vehicle 100, the current gear stage of the transmission 18, and the maximum target driving force TFm.

[0080] Next, in step S520, the on-demand target gear stage calculation unit 133 obtains the current vehicle speed Va of the electric vehicle 100 and the maximum achievable driving force RF for the current gear stage of the transmission 18. The maximum achievable driving force RF can be obtained from the output characteristics MF of the electric vehicle 100 and the operating range RU of each gear stage. For example, Figure 4 shows the maximum achievable driving forces RF-2 and RF-3 for the cases where the current gear stage of the transmission 18 is 2nd and 3rd, respectively. The output characteristics MF of the electric vehicle 100 and the operating range RU of each gear stage may be managed in advance by the computer program 104. The on-demand target gear stage calculation unit 133 can obtain the maximum achievable driving force RF from the current vehicle speed Va of the electric vehicle 100 by referring to the output characteristics MF and operating range RU corresponding to the current gear stage of the transmission 18.

[0081] Next, in step S530, the on-demand target gear stage calculation unit 133 determines whether the maximum target driving force TFm is greater than the maximum realized driving force RF. If the maximum target driving force TFm is less than or equal to the maximum realized driving force RF (step S530; No), the on-demand target gear stage calculation unit 133 calculates the on-demand target gear stage OG according to the shift schedule, similar to the normal mode (step S540). This is because, if the maximum target driving force TFm is less than or equal to the maximum realized driving force RF, the aforementioned problematic events will not occur even without downshifting the gear stage of the transmission 18. On the other hand, if the maximum target driving force TFm is greater than the maximum realized driving force RF (step S530; Yes), the process proceeds to step S550.

[0082] In step S550, the on-demand target gear stage calculation unit 133 determines the gear stage (designated gear stage) of the transmission 18 to which the downshift will occur. For example, the on-demand target gear stage calculation unit 133 designates the gear stage in which the maximum realized driving force RF is equal to or greater than the maximum target driving force TFm as the designated gear stage. In this case, the on-demand target gear stage calculation unit 133 sequentially acquires the maximum realized driving force RF for each gear stage from the current gear stage toward the lower speed gear stage, and designates the gear stage in which the acquired maximum realized driving force RF is equal to or greater than the maximum target driving force TFm as the designated gear stage. Alternatively, the on-demand target gear stage calculation unit 133 may designate the gear stage in which the gear ratio is greatest as the designated gear stage. In this case, the on-demand target gear stage calculation unit 133 designates the gear stage in which the maximum realized driving force RF is greatest as the designated gear stage.

[0083] After step S550, in step S560, the on-demand target gear stage calculation unit 133 determines whether it is the timing (specified timing) to downshift the gear stage of the transmission 18. The specified timing is set to the timing before the on-demand target driving force OF exceeds the maximum realized driving force RF. Specific examples of the specified timing include the following:

[0084] The first specific example concerns the case where the target virtual mobility is a virtual mobility with a gear shift function. The specified timing in the first specific example is when the target virtual mobility shifts down. When the target virtual mobility is a virtual mobility with a gear shift function, it is considered that the target virtual mobility shifts down before the on-demand target driving force OF (or virtual acceleration VA) increases significantly. Therefore, the timing when the target virtual mobility shifts down is before the on-demand target driving force OF exceeds the maximum realized driving force RF. Furthermore, according to the first specific example, the gear shift of the transmission 18 will occur at the same timing as the shift down of the target virtual mobility. This makes it possible to match the timing of the shift shock associated with the shift down, thereby further improving the reproducibility of the acceleration characteristic VC of the target virtual mobility. The on-demand target gear calculation unit 133 can determine when the target virtual mobility shifts down by comparing the current gear of the target virtual mobility obtained from the target on-demand model with the target gear.

[0085] The second specific example relates to the operating state of the accelerator pedal 22, which is an accelerator operating device. The specified timing for the second specific example is when a specific operation is performed that significantly changes the operating state of the accelerator pedal 22. It is considered that the operating state of the accelerator pedal 22 has changed significantly before the on-demand target driving force OF (or virtual acceleration VA) increases significantly. Therefore, it can be said that when an operation that significantly changes the operating state of the accelerator pedal 22 is performed, it is the timing before the on-demand target driving force OF exceeds the maximum realized driving force RF. A specific operation is, for example, an operation in which the increase in accelerator opening angle exceeds a threshold. Another example is an operation in which the accelerator opening angle becomes 100%. Specific operations may be managed in advance by the computer program 104. The on-demand target gear stage calculation unit 133 can determine when a specific operation has been performed by acquiring the operating state of the accelerator pedal 22.

[0086] As another specific example, the specified timing can also be set to when the predicted value of the on-demand target driving force OF a certain time in advance exceeds the maximum realized driving force RF. The predicted value of the on-demand target driving force OF can be obtained from the simulation of the driving environment of the target virtual mobility using the target on-demand model.

[0087] In this embodiment, the specified timing is set in this manner. The specified timing may be set by combining the specific examples described above.

[0088] If the on-demand target gear stage calculation unit 133 determines that it is not the specified timing (step S560; No), it calculates the on-demand target gear stage OG according to the shift schedule, just as in normal mode (step S540). On the other hand, if the on-demand target gear stage calculation unit 133 determines that it is the specified timing (step S560; Yes), it sets the specified gear stage as the on-demand target gear stage OG.

[0089] As described above, the on-demand target gear stage calculation unit 133 according to this embodiment performs processing. According to this embodiment, when the maximum target driving force TFm is greater than the maximum realized driving force RF, the gear stage of the transmission 18 is shifted down to the specified gear stage at a specified timing before the on-demand target driving force OF exceeds the maximum realized driving force RF. This makes it possible to suppress gear stage downshifts that do not occur in the operation of the target virtual mobility due to the driver's driving operation. As a result, the reproducibility of the acceleration characteristics VC of the target virtual mobility can be improved.

[0090] Figure 9 shows an embodiment of the drive control device 101a according to this embodiment. Figure 9 shows the same situation as shown in Figure 7. That is, the example shown in Figure 9 shows the case where the driver performs a kickdown at time t0. In Figure 9, the time change of the virtual gear stage of the target virtual mobility is further shown compared to the case shown in Figure 7. That is, in the example shown in Figure 9, the target virtual mobility is a virtual mobility with a gear shift function. In Figure 9, compared to the case shown in Figure 7, it can be seen that the gear shift down is performed at a specified timing DT before time t1 when the target virtual mobility shifts down (from Nth gear to N-1th gear). As a result, at time t1 when the on-demand target driving force OF increases significantly, the gear stage is already in 3rd gear, so the driving force (acceleration) of the electric vehicle 100 does not stagnate between time t1 and time t2. As a result, there is almost no discrepancy between the driving force of the electric vehicle 100 and the on-demand target driving force OF. In this way, according to this embodiment, the reproducibility of the acceleration characteristics VC of the target virtual mobility can be improved.

[0091] In the processing related to step S530 of the processing flow described above, the on-demand target gear stage calculation unit 133 may be configured to add a predetermined margin to the maximum target driving force TFm and determine whether that value is greater than the maximum achievable driving force RF. This makes it possible to make a decision to downshift to a specified gear stage at a stage where there is sufficient margin.

[0092] 4.3 Example Configuration of an On-Demand Model The following describes an example of the configuration of an on-demand model 200 managed by the on-demand model database D10. Figure 10 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.

[0093] 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 a CONV and an HEV. Therefore, the on-demand model 200 for the CONV and the on-demand model 200 for the HEV will have different specifications for both the control model 210 and the plant model 220. The example shown in Figure 10 specifically illustrates the case where the virtual mobility is an automatic transmission vehicle (AT vehicle) equipped with an internal combustion engine.

[0094] The control model 210 includes a target virtual driving force calculation unit 211 and a request 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 accelerator opening and vehicle speed. For example, the target virtual driving force calculation unit 211 performs the calculation using a map that assigns a target virtual driving force to a combination of accelerator opening and vehicle speed. The request output calculation unit 212 calculates the request output to the powertrain so that the calculated target virtual driving force can be met. The calculated request output includes the target engine torque of the internal combustion engine and the target gear of the transmission. The control model 210 transmits the calculated request output to the plant model 220.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] As explained above, an on-demand model 200 can be configured. The on-demand model 200 shown in Figure 10 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.

[0101] 4.4 Modified Examples of the On-Demand Target Driving Force Calculation Unit The on-demand target driving force calculation unit 132 may adopt the following modified configuration. In the following description, parts that overlap with the above content have been omitted as appropriate.

[0102] As described above, according to this embodiment, when the maximum target driving force TFm is greater than the maximum realized driving force RF, the gear of the transmission 18 is shifted down to a specified gear, thereby improving the reproducibility of the acceleration characteristics VC of the target virtual mobility. On the other hand, even when the gear of the transmission 18 is shifted down to a specified gear, there is a difference between the virtual driving force of the target virtual mobility and the driving force of the electric vehicle 100, which can reduce the reproducibility of the acceleration characteristics VC of the target virtual mobility. Therefore, to address this issue, the on-demand target driving force calculation unit 132 may be configured to add the difference obtained by subtracting the current driving force of the electric vehicle 100 from the virtual driving force of the target virtual mobility to the on-demand target driving force OF when the gear of the transmission 18 is in a specified gear.

[0103] Figure 11 is a flowchart showing the processing flow of the on-demand target driving force calculation unit 132 (more specifically, the processor 102) in the modified example. The processing flow shown in Figure 11 is executed repeatedly at a predetermined processing cycle.

[0104] In step S710, the on-demand target driving force calculation unit 132 determines whether the gear of the transmission 18 is the specified gear. If the gear of the transmission 18 is not the specified gear (step S710; No), the on-demand target driving force calculation unit 132 terminates the process without correcting the on-demand target driving force OF. If the gear of the transmission 18 is the specified gear (step S710; Yes), the process proceeds to step S720.

[0105] In step S720, the on-demand target driving force calculation unit 132 obtains the current driving force of the electric vehicle 100. For example, the on-demand target driving force calculation unit 132 can obtain the current driving force from the current acceleration of the electric vehicle 100.

[0106] Next, in step S730, the on-demand target driving force calculation unit 132 acquires the virtual driving force of the target virtual mobility. The on-demand target driving force calculation unit 132 can acquire the virtual driving force of the target virtual mobility from the virtual driving environment calculation unit 131.

[0107] Next, in step S740, the on-demand target driving force calculation unit 132 adds the difference obtained by subtracting the current driving force of the electric vehicle 100 from the virtual driving force of the target virtual mobility to the on-demand target driving force OF. After step S740, this process is completed.

[0108] In the modified version, the difference between the virtual driving force of the target virtual mobility and the current driving force of the electric vehicle 100 is added to the on-demand target driving force OF. This reduces the difference between the virtual driving force of the target virtual mobility and the driving force of the electric vehicle 100. As a result, the reproducibility of the acceleration characteristics VC of the target virtual mobility can be further improved.

[0109] The processing flow described above can also be executed by the arbitration unit 140. In this case, the arbitration unit 140 executes the processing flow described above in process 141 when the electric vehicle 100 is in on-demand mode. Then, in step S740, the arbitration unit 140 adds the difference obtained by subtracting the current driving force of the electric vehicle 100 from the virtual driving force of the target virtual mobility to the target driving force TF.

[0110] 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 21 and the instrument 23. 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 21 and the instrument 23 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.

[0111] Figure 12 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 21 and instrument 23 according to the driving environment of the target virtual mobility.

[0112] 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.

[0113] 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 6.

[0114] 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.

[0115] 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.

[0116] The speaker control unit 180 controls the output of the speaker 21 based on the sound data transmitted from the virtual sound generation unit 170. As a result, a virtual sound is output from the speaker 21.

[0117] The instrument control unit 190 controls the instrument 23 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 23 based on the obtained information. As a result, the virtual display information is displayed on the instrument 23.

[0118] 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 21 and virtual display information is shown on the instrument panel 23. This further enhances the driver's sense of realism, making them feel as if they are driving the target virtual mobility device.

[0119] 6. Others The technical features of this embodiment are not limited to BEVs, but are broadly applicable to any electric vehicle having an electric motor as a drive source. For example, the technical features of this embodiment are applicable to HEVs and PHEVs that have a mode of running solely on the driving force of the electric motor. They are also applicable to FCEVs that supply electric energy generated by a fuel cell to the electric motor. [Explanation of Symbols]

[0120] 2 Electric motor 14 batteries 16 Inverters 18-speed transmission 22 Accelerator pedal 24 Brake pedal 100 Electric Vehicles 101 Control device 102 processors 103 Storage device 200 On-Demand Models DT specified timing RF Maximum Achievable Driving Force TFm (Maximum Target Driving Force) VA (Virtual Acceleration)

Claims

1. An electric vehicle having an electric motor as its driving source, Operating components used for operation, A transmission that changes the output of the electric motor according to the gear ratio and transmits it to the drive wheels of the electric vehicle, 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 and the gear stages of the transmission, 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 target driving force of the electric vehicle is calculated so that the acceleration of the electric vehicle is the virtual acceleration. The output of the electric motor is controlled to provide the target driving force to the electric vehicle. The maximum target driving force, which is the maximum value of the target driving force that can be achieved at the current vehicle speed of the electric vehicle, is obtained. The maximum possible driving force, which is the maximum driving force that the electric vehicle can output at the current vehicle speed and the current gear position of the transmission, is obtained. When the maximum target driving force is greater than the maximum achievable driving force, the gear of the transmission is shifted down to the specified gear at the specified timing. It is configured in such a way Electric vehicle.

2. An electric vehicle according to claim 1, The designated gear stage is the gear stage in which the maximum achievable driving force is equal to or greater than the maximum target driving force, or the gear stage in which the gear ratio is maximized. Electric vehicle.

3. An electric vehicle according to claim 1, When the target virtual mobility is a virtual mobility having a gear shift function, the specified timing is when the target virtual mobility shifts down. Electric vehicle.

4. An electric vehicle according to claim 1, The aforementioned operating member includes an accelerator operating device, The specified timing is when a specific operation is performed that significantly changes the operating state of the accelerator control device. Electric vehicle.

5. An electric vehicle according to claim 1, When the electric vehicle is in on-demand mode, the one or more processors further: When the gear position of the transmission is the designated gear position, The current driving force of the electric vehicle is obtained, Using the target on-demand model, the virtual driving force of the target virtual mobility in response to the driver's driving operations is obtained. The difference obtained by subtracting the current driving force from the virtual driving force is added to the target driving force. It is configured in such a way Electric vehicle.

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