Electric vehicle

Abstract

To provide a technique for accurately reproducing a traveling feeling of a virtual vehicle in an electric vehicle.SOLUTION: The present disclosure relates to an electric vehicle having an electric motor as a drive source. The electric vehicle includes one or more processors configured to control the electric motor to reproduce a behavior of a virtual vehicle different from the electric vehicle. The one or more processors calculate a target torque based on the travel resistance of the virtual vehicle, and control the torque of the electric motor based on the target torque.SELECTED DRAWING: Figure 5

Description

[Technical Field]

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

[0002] Patent Document 1 discloses a driving force control device for a vehicle equipped with a motor as a driving force source. The driving force control device can reproduce the driving force of a virtual vehicle with a different powertrain on the vehicle. The virtual vehicles that can be reproduced include vehicles with transmissions. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-030360 Summary of the Invention [Problem to be solved by the invention]

[0004] As disclosed in Patent Document 1, a technique is known for an electric vehicle that uses an electric motor as a driving force source to reproduce the driving force of a virtual vehicle by controlling the torque of the electric motor. In such a vehicle, if the driving feel of the virtual vehicle can be accurately reproduced, the driver's satisfaction can be further increased. [Means for solving the problem]

[0005] A first aspect of the present disclosure relates to an electric vehicle having an electric motor as a drive source. The electric vehicle is equipped with one or more processors that control the electric motor to reproduce the behavior of a virtual vehicle different from the electric vehicle. The one or more processors calculate a target torque based on the running resistance of the virtual vehicle and control the torque of the electric motor based on the target torque.

[0006] A second aspect of the present disclosure relates to a control method for controlling an electric vehicle having an electric motor as a drive source, the control method including: acquiring the running resistance of a virtual vehicle different from the electric vehicle; calculating a target torque for reproducing the behavior of the virtual vehicle based on the running resistance of the virtual vehicle; and controlling the torque of the electric motor based on the target torque. [Effects of the Invention]

[0007] According to the first and second aspects of the present disclosure, a target torque is calculated based on the running resistance of a virtual vehicle, and the torque of the electric motor is controlled based on the target torque. By using the running resistance of the virtual vehicle to calculate the target torque, it is possible to reproduce the driving feel of the virtual vehicle, which differs depending on the running resistance, and to increase the satisfaction of the driver. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of an electric vehicle according to an embodiment of the present disclosure. [Figure 2] FIG. 1 is a tree diagram showing an example of a selection input received by an HMI regarding a control mode of an electric vehicle. [Figure 3] FIG. 2 is a diagram illustrating an example of a functional configuration of a control device that functions as a motor control device. [Figure 4] FIG. 4 is a diagram illustrating an example of a functional configuration of an on-demand mode torque calculation unit. [Figure 5] FIG. 10 is a diagram illustrating an example of a method for calculating a target torque. [Figure 6] FIG. 1 is a diagram illustrating an example of the configuration of an electric vehicle equipped with a pseudo speed change operation member. DETAILED DESCRIPTION OF THE INVENTION

[0009] Embodiments of the present disclosure will be described with reference to the accompanying drawings.

[0010] 1. Electric vehicle power system configuration 1 is a diagram schematically illustrating 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.

[0011] The electric vehicle 100 is equipped with an electric motor (M) 2 as a drive source for traveling. The electric motor 2 is, for example, a three-phase AC motor. An output shaft 3 of the electric motor 2 is connected to one end of a propeller shaft 5 via a gear mechanism 4. The other end of the propeller shaft 5 is connected to a drive shaft 7 at the front of the vehicle via a differential gear 6.

[0012] The electric vehicle 100 has driving wheels 8 which are front wheels and driven wheels 12 which are rear wheels. The driving wheels 8 are provided on both ends of the drive shaft 7, respectively.

[0013] The electric vehicle 100 includes a battery (BATT) 14 and an inverter (INV) 16. The battery 14 stores electrical energy for driving the electric motor 2. In other words, the electric vehicle 100 is a battery electric vehicle (BEV) that runs on electrical energy stored in the battery 14. The inverter 16 is, for example, a voltage-type inverter. The inverter 16 controls the motor torque output by the electric motor 2 by PWM control.

[0014] 2. Electric vehicle control system configuration Next, the configuration of the control system of the electric vehicle 100 will be described with reference to FIG.

[0015] The electric vehicle 100 is provided with a vehicle speed sensor 30 for detecting the vehicle speed. At least one of wheel speed sensors (not shown) provided on each of the left and right front wheels 8 and the left and right rear wheels 12 is used as the vehicle speed sensor 30.

[0016] The electric vehicle 100 is equipped with an accelerator pedal stroke sensor 32. The accelerator pedal stroke sensor 32 is provided on the accelerator pedal 22 and outputs a signal indicating the operation state of the accelerator pedal 22. The operation state of the accelerator pedal typically includes the accelerator opening degree and accelerator opening speed. Note that the accelerator pedal 22 is a pedal-type operation device operated by the foot, but the electric vehicle 100 may also be equipped with an accelerator operation device that is operated by hand, such as a lever-type operation device or a dial-type operation device, instead of the accelerator pedal 22.

[0017] The electric vehicle 100 also includes a brake pedal stroke sensor 34. The brake pedal stroke sensor 34 is provided on the brake pedal 24 and outputs a signal indicating the operation state of the brake pedal 24. The operation state of the brake pedal 24 typically includes the brake opening degree and the brake opening speed. Note that the brake pedal 24 is a pedal-type operation device operated by the foot, but the electric vehicle 100 may also be provided with a lever-type operation device or a dial-type operation device operated by hand instead of the brake pedal 24 as the brake operation device.

[0018] The accelerator pedal 22 and the brake pedal 24 are each one of the driving operation members used to drive the electric vehicle 100. In addition, the electric vehicle 100 may be equipped with various other driving operation members, such as a steering wheel for steering.

[0019] The electric vehicle 100 is equipped with a rotational speed sensor 40. The rotational speed sensor 40 is provided in the electric motor 2 and outputs a signal indicating the rotational speed of the electric motor 2.

[0020] 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 a battery 14. The battery management system 10 has a function of estimating the state of charge (SOC) of the battery 14.

[0021] The electric vehicle 100 is equipped with a human-machine interface (HMI) 20 as an interface with the driver. The HMI 20 presents various types of information to the driver by display and sound, and also accepts various inputs from the driver. The HMI 20 is composed of a display (e.g., a multi-information display, a meter display), switches, a touchpad, a speakerphone, a touchscreen, etc. For example, the HMI 20 displays various types of information on a display and accepts inputs from the driver regarding the displayed content by operating a switch. Alternatively, the HMI 20 displays various types of information on a touchscreen and accepts inputs from the driver regarding the displayed content by touching the touchscreen.

[0022] The electric vehicle 100 is equipped with a control device 101. Various sensors and devices to be controlled that are mounted on the electric vehicle 100 are connected to the control device 101 via an on-board network such as a controller area network (CAN). In addition to the vehicle speed sensor 30, accelerator pedal stroke sensor 32, brake pedal stroke sensor 34, and rotational speed sensor 40, various other sensors are mounted on the electric vehicle 100 and connected to the control device 101 via the on-board network. For example, the sensors mounted on the electric vehicle 100 may include a gradient sensor that detects the gradient of the road surface on which the electric vehicle 100 is traveling.

[0023] The control device 101 generates control signals related to 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 includes at least a processing circuit 102 and a storage device 103.

[0024] The processing circuitry 102 performs various processes. The processing circuitry 102 may be, for example, a general-purpose processor, a special-purpose processor, a central processing unit (CPU), a graphics processing unit (GPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), an integrated circuit, a conventional circuit, or a combination of one or more of these. A processor including transistors and other circuits is an example of the processing circuitry 102. The processing circuitry 102 may also be referred to as circuitry or processing circuitry. Circuitry is hardware that is programmed to realize or executes the functions described in this disclosure.

[0025] The storage device 103 stores various information necessary for the processing circuit 102 to execute processing. The storage device 103 is configured with a recording medium such as a RAM (Random Access Memory), a ROM (Read Only Memory), an SSD (Solid State Drive), or an HDD (Hard Disk Drive). The storage device 103 stores a computer program 104 executable by the processing circuit 102 and various data 105. The computer program 104 is configured with a plurality of instructions that describe the processing to be executed by the processing circuit 102. The computer program 104 may be recorded on a computer-readable recording medium. The functions of the control device 101 are realized by cooperation between the processing circuit 102, which executes the computer program 104, and the storage device 103.

[0026] The control device 101 according to this embodiment has at least two control modes, a normal mode and an on-demand mode, for controlling the electric vehicle 100. The control of the electric vehicle 100 performed by the control device 101 changes depending on the selected control mode. The control modes of the electric vehicle 100 will be described below.

[0027] 3. Electric vehicle control mode As described above, there are at least two control modes for the electric vehicle 100: normal mode and on-demand mode. The normal mode is a control mode in which the electric vehicle 100 is operated as a normal BEV. When the normal mode is selected, the control device 101 controls the electric vehicle 100 so that it operates as a normal BEV. On the other hand, the on-demand mode is a control mode in which the vehicle behavior of a virtual vehicle (hereinafter referred to as the "target virtual vehicle") selected by the driver from among multiple virtual vehicles is reproduced by the electric vehicle 100. When the on-demand mode is selected, the control device 101 controls the electric vehicle 100 so as to mimic the vehicle behavior of the target virtual vehicle.

[0028] The plurality of virtual vehicles that the driver can select include various vehicles with different acceleration characteristics in response to the driver's driving operations. Each virtual vehicle may be a model of an actual vehicle, or may be a model of a vehicle that does not actually exist.

[0029] The control mode is selected by the driver operating the HMI 20. The HMI 20 is configured to receive a control mode selection input from the driver. The HMI 20 is also configured to receive a selection input from the driver regarding a target virtual vehicle.

[0030] 2 is a tree diagram showing an example of a selection input received by the HMI 20. For example, the HMI 20 receives a selection input from the driver via a display or a touch screen in accordance with the tree shown in FIG. 2 as follows:

[0031] First, the HMI 20 displays a setting menu screen on the display or touch screen in accordance with the driver's operation. The initial screen of the setting menu screen displays the option "Control Mode." The option "Control Mode" is an option for receiving a control mode selection input from the driver.

[0032] When the option "Control Mode" is selected, the options "Normal Mode" and "On-Demand Mode" are then displayed on the settings menu screen. When the option "Normal Mode" is selected, the control mode is switched to normal mode, and control is performed as in a normal BEV. On the other hand, when the option "On-Demand Mode" is selected, the control mode is switched to on-demand mode.

[0033] In the on-demand mode, the driver can select a target virtual vehicle to be reproduced in the electric vehicle 100. When the option "on-demand mode" is selected, the option "target virtual vehicle" is then displayed on the setting menu screen. The option "target virtual vehicle" is an option for receiving a selection input of a target virtual vehicle from the driver.

[0034] When the option "target virtual vehicle" is selected, the settings menu screen displays options "CONV" and "HEV." The options "CONV" and "HEV" each indicate a classification of multiple virtual vehicles that can be selected in on-demand mode. CONV is a classification that indicates a conventional internal combustion engine vehicle. HEV is a classification that indicates a hybrid electric vehicle. When the option "CONV" is selected, the settings menu screen then displays options "virtual vehicle A," "virtual vehicle B," and "virtual vehicle C." Virtual vehicle A, virtual vehicle B, and virtual vehicle C are virtual vehicles classified as CONV among the multiple selectable virtual vehicles. Similarly, when the option "HEV" is selected, the settings menu screen then displays options "virtual vehicle D" and "virtual vehicle E." Virtual vehicle D and virtual vehicle E are virtual vehicles classified as HEV among the multiple selectable virtual vehicles. When the driver selects one of these options, the corresponding virtual vehicle is set as the target virtual vehicle.

[0035] Note that the classification of the multiple virtual vehicles in the above description is an example, and the options related to the classification may be changed as appropriate. For example, the options related to the classification may further include an option indicating a plug-in hybrid electric vehicle or a fuel cell electric vehicle. For example, the options related to the classification may include an option indicating a BEV, and it may be possible to select an electric vehicle other than electric vehicle 100 as the target virtual vehicle. For example, the options related to the classification may indicate other classifications, such as a classification related to the type of internal combustion engine installed (e.g., inline-four supercharged engine, flat-six engine, V12 engine). Alternatively, when the option "on-demand mode" is selected, the options related to the virtual vehicle may be displayed without displaying the options related to the classification.

[0036] Furthermore, the name displayed on the setting menu screen for each option may be appropriately set in consideration of ease of understanding by the driver. For example, for an option related to a virtual vehicle, the displayed name may be a more specific name, such as the model name or product name, that allows the driver to easily imagine the virtual vehicle.

[0037] As described 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.

[0038] The control device 101 according to this embodiment functions as a motor control device that controls the electric motor 2 in accordance with at least the driver's driving operation with respect to the control of the electric vehicle 100. More specifically, the processing circuit 102 executes a computer program 104 for controlling an electric motor stored in a storage device 103, causing the control device 101 to function as a motor control device. The control of the electric vehicle 100 by the motor control device will be described below.

[0039] 4.Motor control device 3 is a diagram showing an example of the functional configuration of the motor control device 101a. The motor control device 101a calculates a target torque for the drive wheels in accordance with the driver's driving operation. The motor control device 101a then controls the electric motor 2 via the inverter 16 so that the calculated target torque is generated at the drive wheels.

[0040] Signals from the HMI 20 and the sensor system 50 are input to the motor control device 101a. The sensor system 50 includes a vehicle speed sensor 30, an accelerator pedal stroke sensor 32, a brake pedal stroke sensor 34, a rotational speed sensor 40, and a battery management system 10. The sensor system 50 may also include other sensors not shown. For example, the sensor system 50 may 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, a gradient sensor for detecting the gradient of the road surface, a sensor for detecting the ambient environment of the electric vehicle 100 (e.g., a camera, radar, LiDAR), etc.

[0041] The signals input from the HMI 20 to the motor control device 101a include a signal indicating the control mode selected by the driver and a signal indicating the target virtual vehicle selected by the driver. The signals input from the sensor system 50 to the motor control device 101a include a signal indicating the vehicle speed of the electric vehicle 100, a signal indicating the operation state of the accelerator pedal 22, a signal indicating the operation state of the brake pedal 24, a signal indicating the rotational speed of the electric motor 2, and a signal indicating the state of the battery 14 (e.g., cell voltage, current, temperature, SOC).

[0042] The motor control device 101a includes, as functional blocks, a mode information acquisition unit 110, an on-demand mode torque calculation unit 120, a normal mode torque calculation unit 130, a target torque switching unit 140, and an electric motor control unit 150. These functional blocks are realized by cooperation between a processing circuit 102 that executes a computer program 104 and a storage device 103.

[0043] The mode information acquisition unit 110 receives a signal from the HMI 20 and acquires information about whether the normal mode or the on-demand mode is selected. Furthermore, if the on-demand mode is selected, the mode information acquisition unit 110 acquires information about the target virtual vehicle. The mode information acquisition unit 110 then transmits information about the selected control mode to the target torque switching unit 140 and transmits information about the selected target virtual vehicle to the on-demand mode torque calculation unit 120.

[0044] The on-demand mode torque calculation unit 120, which has acquired information about the target virtual vehicle, calculates a target torque based on signals from the sensor system 50 to reproduce the behavior of the target virtual vehicle in response to the driver's driving operation in the electric vehicle 100.

[0045] The normal mode torque calculation unit 130 calculates a target torque for operating the electric vehicle 100 as a normal BEV based on signals from the sensor system 50. Specifically, the normal mode torque calculation unit 130 calculates the target torque using a map that uses the accelerator opening of the accelerator pedal 22 and the rotational speed of the electric motor 2 as parameters. The calculation of the target torque by the normal mode torque calculation unit 130 may further use the brake opening of the brake pedal 24 and the SOC of the battery 14 as parameters. However, in this embodiment, the processing performed by the normal mode torque calculation unit 130 is not particularly limited. Other suitable known techniques may be applied to the processing performed by the normal mode torque calculation unit 130.

[0046] Based on signals from the sensor system 50, the on-demand mode torque calculation unit 120 calculates a target torque for reproducing the behavior of the target virtual vehicle in the electric vehicle 100. Details of the processing in the on-demand mode torque calculation unit 120 will be described later.

[0047] The target torque switching unit 140 switches the target torque for controlling the electric motor 2 depending on the selected control mode. The target torque switching unit 140 acquires information on the selected control mode from the mode information acquisition unit 110. If the on-demand mode is selected, the target torque switching unit 140 transmits the target torque calculated by the on-demand mode torque calculation unit 120 to the electric motor control unit 150, and if the normal mode is selected, the target torque switching unit 140 transmits the target torque calculated by the normal mode torque calculation unit 130 to the electric motor control unit 150.

[0048] Note that when the on-demand mode is selected, the normal mode torque calculation unit 130 may be configured not to execute any processing. Similarly, when the normal mode is selected, the on-demand mode torque calculation unit 120 may be configured not to execute any processing.

[0049] The target torque calculated by the on-demand mode torque calculation unit 120 or the normal mode torque calculation unit 130 is input to the electric motor control unit 150 via the target torque switching unit 140. The electric motor control unit 150 changes the motor torque of the electric motor 2 so that the drive wheel torque becomes the target torque. More specifically, the electric motor control unit 150 generates a control signal for the inverter 16 in accordance with the input target torque. Then, the electric motor control unit 150 changes the motor torque output by the electric motor 2 via PWM control by the inverter 16.

[0050] In this way, the motor control device 101a controls the electric motor 2 according to the target torque corresponding to the control mode. Due to this control by the motor control device 101a, the acceleration characteristics of the electric vehicle 100 when the on-demand mode is selected will simulate the acceleration characteristics of the target virtual vehicle, and the acceleration characteristics of the electric vehicle 100 when the normal mode is selected will be the acceleration characteristics of a normal BEV.

[0051] 5. Calculation of target torque in on-demand mode The on-demand mode torque calculation unit 120 calculates the target torque so that the acceleration characteristics of the target virtual vehicle in response to the driver's driving operation are reproduced in the electric vehicle 100. As a result, the acceleration characteristics of the electric vehicle 100 when the on-demand mode is selected change to various patterns according to the target virtual vehicle as the target virtual vehicle is changed. The driver can enjoy the driving feel of various virtual vehicles in the on-demand mode. The method for calculating the target torque in the on-demand mode will be described below with reference to FIGS. 4 and 5.

[0052] Fig. 4 is a diagram showing an example of the functional configuration of on-demand mode torque calculation unit 120. Fig. 5 shows an example of a calculation method when the target torque calculated by the functional configuration of Fig. 4 is expressed as a calculation formula. Calculation method A, which takes running resistance into consideration, is the calculation method in this embodiment. For comparison, Fig. 5 also shows a calculation method for the target torque when running resistance is not taken into consideration as calculation method B.

[0053] The on-demand mode torque calculation unit 120 includes, as functional blocks, a base torque calculation unit 121, a correction torque calculation unit 122, and a target torque calculation unit 123. The on-demand mode torque calculation unit 120 is also configured to be able to access the vehicle model database D10.

[0054] The vehicle model database D10 is a database that manages a plurality of vehicle models 200 that are models of a plurality of virtual vehicles. The vehicle model database D10 is realized as data 105 stored in the storage device 103. New vehicle models 200 may be downloaded to the vehicle model database D10 as needed. In the example shown in FIG. 4, the vehicle model database D10 manages three vehicle models 200-A, 200-B, and 200-C. Each vehicle model 200 is a model that receives the driver's driving operation and the running state of the electric vehicle 100 as input, and simulates the behavior of the virtual vehicle in response to the driver's driving operation, particularly the operation of the accelerator pedal 22.

[0055] Typically, each vehicle model 200 includes a powertrain model that simulates the powertrain of the virtual vehicle. The powertrain model is a model for reproducing the torque output from the powertrain of the virtual vehicle based on at least the operation of the accelerator pedal 22 input by the driver. Hereinafter, in this specification, the output torque of the powertrain of the virtual vehicle reproduced by the powertrain model of the virtual vehicle is referred to as virtual torque.

[0056] If the target virtual vehicle is an internal combustion engine vehicle, the powertrain model may include an engine model and a transmission model. The engine model calculates a virtual engine torque (virtual engine torque) output from the engine of the target virtual vehicle based on the driver's operation of the accelerator pedal 22, and the transmission model outputs a virtual gear ratio (virtual gear ratio) of the target virtual vehicle. In this case, the virtual torque is calculated as the product of the virtual engine torque and the virtual gear ratio.

[0057] Each vehicle model 200 also has parameters 201 related to the behavior of the virtual vehicle. The parameters 201 include running resistance, vehicle weight, wheel diameter, number of gears, gear ratio at each gear, differential ratio, maximum engine torque, etc.

[0058] The base torque calculation unit 121 calculates a torque for reproducing the output of the powertrain of the target virtual vehicle based on the driving operation of the driver in the electric vehicle 100. Hereinafter in this specification, this torque calculated by the base torque calculation unit 121 will be referred to as the base torque. The base torque is calculated as the product of the virtual torque and a specification absorption coefficient. The specification absorption coefficient is a coefficient for absorbing differences in the specifications of the target virtual vehicle and the electric vehicle 100. An example of a method for calculating the specification absorption coefficient is shown in equation (c).

[0059] The base torque calculation unit 121 acquires information on the target virtual vehicle STV selected by the driver from the mode information acquisition unit 110. Then, the base torque calculation unit 121 references the vehicle model database D10 and reads out a vehicle model 200 (target vehicle model) corresponding to the target virtual vehicle STV. The vehicle model 200 read out by the base torque calculation unit 121 includes parameters 201 of the target virtual vehicle. In the example shown in FIG. 4, virtual vehicle B is selected as the target virtual vehicle, and the base torque calculation unit 121 reads out the target vehicle model 200-B from the vehicle model database D10.

[0060] The base torque calculation unit 121 uses the read target vehicle model to calculate a virtual torque to be output from the powertrain of the target virtual vehicle STV in response to operation of the accelerator pedal 22 by the driver. More specifically, the base torque calculation unit 121 receives signals from the sensor system 50 and acquires information on the operation state AS of the accelerator pedal 22 (e.g., accelerator opening) and information on the running state RS of the electric vehicle 100 (e.g., vehicle speed). Then, by using this information as input to the target vehicle model and simulating the operation of the powertrain of the target virtual vehicle STV, the base torque calculation unit 121 calculates a virtual torque to be output from the powertrain of the target virtual vehicle STV. Note that other information such as the operation state of the brake pedal 24, the steering angle of the steering wheel, and the yaw rate of the electric vehicle 100 may also be input to the target vehicle model depending on the configuration of the target vehicle model.

[0061] The base torque calculation unit 121 then calculates the base torque by multiplying the virtual torque by the specification absorption coefficient. The calculated base torque is sent to the target torque calculation unit 123.

[0062] The correction torque calculation unit 122 calculates torque for correcting the difference in running resistance between the electric vehicle 100 and the target virtual vehicle. The correction torque calculation unit 122 first obtains the running resistances of the electric vehicle 100 and the target virtual vehicle.

[0063] The running resistance acquired here includes air resistance, rolling resistance, gradient resistance, acceleration resistance, and at least a portion of mechanical losses generated by the powertrain configuration. Values ​​necessary to calculate the running resistance of the electric vehicle 100 are stored as data 105 in the storage device 103. The correction torque calculation unit 122 may use the values ​​stored in the storage device 103 as they are, or may calculate the running resistance using the values ​​stored in the storage device 103 and values ​​acquired in real time by the sensor system 50. Values ​​acquired in real time include, for example, vehicle speed, gradient, total vehicle weight, etc. Values ​​necessary to calculate the running resistance can be experimentally obtained in advance using known methods.

[0064] For example, values ​​required for calculating running resistance may be determined by the ABC method and stored in the storage device 103. Then, running resistance may be calculated based on the pre-stored values ​​and the vehicle speed acquired from the vehicle speed sensor 30. The ABC method can calculate running resistance including air resistance, rolling resistance, and mechanical loss. Alternatively, values ​​required for calculating running resistance may be determined by other methods and stored in the storage device 103. Then, running resistance may be calculated based on the values ​​stored in the storage device 103 and the values ​​acquired from the sensor system 50.

[0065] The values ​​required to calculate the running resistance of the target virtual vehicle are included in the parameters 201. Similarly, the values ​​required to calculate the running resistance of the target virtual vehicle can also be experimentally determined in advance. Alternatively, if the target virtual vehicle is a vehicle that does not exist in reality, the values ​​may be determined by simulation or the like. The correction torque calculation unit 122 may use the values ​​included in the parameters 201 as they are, or may calculate the running resistance using the values ​​included in the parameters 201 and values ​​acquired in real time by the sensor system 50. For example, the running resistance may be calculated using the values ​​included in the parameters 201 and the vehicle speed of the electric vehicle 100.

[0066] In this way, the correction torque calculation unit 122 calculates the running resistance generated in the electric vehicle 100 and the running resistance generated when the electric vehicle 100 is assumed to be the target virtual vehicle, and calculates a correction torque based on the difference in running resistance between the electric vehicle 100 and the target virtual vehicle from these values. The correction torque may be, for example, the difference between a running resistance converted torque obtained by converting the running resistance of the electric vehicle 100 into the driving wheel torque of the electric vehicle 100 and a running resistance converted torque obtained by converting the running resistance of the target virtual vehicle into the driving wheel torque of the electric vehicle 100. Examples of methods for calculating the running resistance converted torque of the electric vehicle 100 and the running resistance converted torque of the target virtual vehicle are shown in equations (e), (f), and (g). The calculated correction torque is transmitted to the target torque calculation unit 123.

[0067] The target torque calculation unit 123 calculates the target torque based on the base torque calculated by the base torque calculation unit 121 and the correction torque calculated by the correction torque calculation unit 122. For example, as shown in equation (a), the sum of the base torque and the correction torque may be set as the target torque. The target torque is calculated in this manner, and the electric motor 2 is controlled based on the calculated target torque.

[0068] 6.Effects As described above, in the electric vehicle 100 according to this embodiment, in the on-demand mode, the target torque is calculated taking into account the running resistance, and the electric motor 2 is controlled. The effect of calculating the target torque based on the running resistance in this manner will be described.

[0069] Differences in acceleration characteristics between vehicles are generally due to differences in the configuration of the powertrain from the drive source to the drive wheels. Therefore, one possible method for calculating the target torque is to calculate the target torque so as to simply simulate the configuration of the powertrain of the target hypothetical vehicle, as in calculation method B in Figure 5.

[0070] However, the torque output from the powertrain is not the only factor that affects the acceleration characteristics of the target virtual vehicle. Differences in running resistance between vehicles also affect the acceleration characteristics. For example, if a virtual vehicle is heavier and has greater running resistance than the electric vehicle 100, its acceleration will be slower. If such a vehicle is selected as the target virtual vehicle and the torque output from the powertrain is reproduced as is, the acceleration reproduced by the electric vehicle 100 will feel quicker than that of the target virtual vehicle, which may cause the driver to feel uncomfortable. In this way, if only the torque output from the powertrain is reproduced without taking running resistance into consideration, the driver may feel uncomfortable. In particular, in a range where the operation amount of the accelerator pedal 22 is small, the running resistance has a large effect on changes in acceleration, which may cause the driver to feel uncomfortable.

[0071] In contrast, in this embodiment, the target torque is calculated taking into account the difference in running resistance between the electric vehicle 100 and the target virtual vehicle. That is, the on-demand mode torque calculation unit 120 calculates the target torque based on a base torque that simulates the powertrain of the target virtual vehicle and a correction torque that corrects the difference in running resistance between the electric vehicle 100 and the target virtual vehicle. This makes it possible to make the acceleration feel of the electric vehicle 100 closer to that of the actual target virtual vehicle than by simply using a target torque that simulates the powertrain of the virtual vehicle. In this way, the vehicle behavior of the virtual vehicle can be reproduced with greater accuracy, thereby improving the satisfaction of drivers who want to experience the driving feel of a virtual vehicle.

[0072] 7. Virtual vehicle example The plurality of virtual vehicles may include a transmission vehicle. When the virtual vehicles include a transmission vehicle, the electric vehicle 100 may be provided with, in addition to the driving operation members used to drive the electric vehicle 100, pseudo gear shift operation members that simulate the operation members used to change gears in a transmission vehicle.

[0073] FIG. 6 shows examples of pseudo gearshift operation members provided in the electric vehicle 100. The pseudo gearshift operation members include a pseudo H-type shifter 25, pseudo paddle shifters 26, and a pseudo clutch pedal 27. The pseudo H-type shifter 25 is an operation member that simulates an H-type shifter of a transmission vehicle, and the driver can select a gear by operating the shift stick of the pseudo H-type shifter 25. The pseudo paddle shifter 26 is an operation member that simulates a paddle shifter of a transmission vehicle, and the driver can increase or decrease the gear by operating the pseudo paddle shifter 26. The pseudo clutch pedal 27 is an operation member that simulates a clutch pedal of a transmission vehicle, and the driver can change the virtual clutch opening within a range from 0% to 100% by operating the pseudo clutch pedal 27.

[0074] These pseudo-speed change operation members are provided with switches that output signals indicating the driver's operation state. The signals output from the respective switches indicating the operation state of the pseudo-speed change operation members may be input to a powertrain model and used to calculate virtual torque. In this way, the motor control device 101a controls the electric motor 2 so as to reproduce the behavior of a transmission vehicle based on the operation of the driving operation members and the pseudo-speed change operation members. [Explanation of symbols]

[0075] 2...electric motor 3...output shaft 4...gear mechanism 5...propeller shaft 6...differential gear 7...drive shaft 8...front wheels 10...battery management system 12...rear wheels 14...battery 16...inverter 22...accelerator pedal 24...brake pedal 25...pseudo H-type shifter 26...pseudo paddle shifter 27...pseudo clutch pedal 30...vehicle speed sensor 32...accelerator pedal stroke sensor 34...brake pedal stroke sensor 40...rotational speed sensor 50...sensor system 100...electric vehicle 101...control device 101a...motor control device 102...processing circuit 103...storage device 104...computer program 105...data 110...mode information acquisition unit 120...on-demand mode torque calculation unit 121...base torque calculation unit 122...corrected torque calculation unit 123...target torque calculation unit 130...normal mode torque calculation unit 140... Target torque switching unit 150... Electric motor control unit 200... Vehicle model 201... Parameter

Claims

1. An electric vehicle having an electric motor as a drive source, one or more processors that control the electric motors to replicate a behavior of a virtual vehicle that is different from the electric vehicle; the one or more processors: Calculating a target torque based on the running resistance of the virtual vehicle; The torque of the electric motor is controlled based on the target torque. An electric vehicle characterized by:

2. 2. The electric vehicle according to claim 1, Further provided is a driving operation member used to drive the electric vehicle, the one or more processors: calculating a base torque for reproducing the torque output from the powertrain of the virtual vehicle based on the operation of the driving operation member; calculating a correction torque based on the running resistance of the virtual vehicle; The target torque is calculated based on the base torque and the correction torque. An electric vehicle characterized by:

3. 3. The electric vehicle according to claim 2, the one or more processors: Calculating the correction torque based on the difference between the running resistance of the electric vehicle and the running resistance of the virtual vehicle An electric vehicle characterized by:

4. 4. The electric vehicle according to claim 2 or 3, the virtual vehicle includes a transmission vehicle; The transmission vehicle further includes a pseudo speed change operation member that simulates an operation member used for speed change operation, The one or more processors control the electric motor based on the operation of the pseudo speed change operating member so as to reproduce the behavior of the transmission vehicle. An electric vehicle characterized by:

5. A control method for controlling an electric vehicle having an electric motor as a drive source, comprising: acquiring a running resistance of a virtual vehicle different from the electric vehicle; calculating a target torque for reproducing a behavior of the virtual vehicle based on the running resistance of the virtual vehicle; controlling the torque of the electric motor based on the target torque; Contains Control method.

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