Vehicle control device

Abstract

To suppress torque variation of an axle and a drive shaft and to decelerate a vehicle more appropriately.SOLUTION: A vehicle control device is used for a vehicle including: a motor for outputting power to a drive shaft; and a braking force application device for applying braking force to a wheel connected to the drive shaft via an axle. The vehicle control device controls the motor and the braking force application device. When a braking request is made during traveling on a wavy road, the vehicle control device predicts a time waveform of a wheel speed while requested braking force based on the braking request is applied, and executes reduction control for controlling the braking force application device so that braking force reduced from the requested braking force is applied from the braking force application device in accordance with a timing of variation in the wheel speed in the predicted time waveform of the wheel speed.SELECTED DRAWING: Figure 4

Description

[Technical field]

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

[0002] Conventionally, as a control device for this type of vehicle, a device has been proposed for use in a vehicle equipped with a motor that outputs power to a drive shaft and a hydraulic braking force application device (brake) that applies braking force to wheels connected to the drive shaft via an axle, and for controlling the brakes (see, for example, Patent Document 1). In this device, when sudden braking is required while the vehicle is traveling on an uneven road, the braking force application device is controlled so that the brake oil pressure becomes equal to or lower than a threshold value. This suppresses torque fluctuations in the axles and drive shafts. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2010-264915 A Summary of the Invention [Problem to be solved by the invention]

[0004] Although the above-mentioned control device suppresses torque fluctuations in the axles and drive shafts, the brake hydraulic pressure is kept below a threshold value, which may result in suppression of deceleration of the vehicle.

[0005] The main objective of the vehicle control device disclosed herein is to suppress torque fluctuations in the axles and drive shafts and to more appropriately decelerate the vehicle. [Means for solving the problem]

[0006] The vehicle control device of the present disclosure employs the following means to achieve the above-mentioned main object.

[0007] The vehicle control device of the present disclosure includes: A vehicle control device is used in a vehicle including a motor that outputs power to a drive shaft and a braking force application device that applies a braking force to a wheel connected to the drive shaft via an axle, the vehicle control device controlling the motor and the braking force application device, When a braking request is made while traveling on an undulating road, a time waveform of a wheel speed when a requested braking force based on the braking request is applied is predicted, and reduction control is performed to control the braking force application device so that a braking force reduced from the requested braking force is applied from the braking force application device in accordance with a timing of fluctuation of the wheel speed in the predicted time waveform of the wheel speed. The gist of the present invention is as follows.

[0008] In the vehicle control device disclosed herein, when a braking request is made while traveling on an undulating road, the time waveform of the wheel speed when a required braking force based on the braking request is applied is predicted, and a reduction control is performed to control the braking force application device so that a braking force reduced from the required braking force is applied from the braking force application device in accordance with the timing of the fluctuation of the wheel speed in the predicted time waveform of the wheel speed. When the vehicle bounces on the undulating road and the wheels spin, that is, when a constant braking force is applied to the wheels when the wheel speed fluctuates, torque fluctuations occur in the axles and drive shafts. Therefore, by reducing the braking force applied to the wheels from the required braking force in accordance with the fluctuation of the wheel speed, the torque fluctuation of the axles and drive shafts can be suppressed compared to a device that applies a constant, relatively large braking force regardless of the fluctuation of the wheel speed. In addition, the vehicle can be decelerated more quickly compared to a device that applies a constant, relatively small braking force regardless of the fluctuation of the wheel speed. As a result, the torque fluctuation of the axles and drive shafts can be suppressed and the vehicle can be decelerated more appropriately.

[0009] In the vehicle control device of the present disclosure, the braking request is a request for sudden braking, and the time waveform of the wheel speed may be predicted based on the time waveform until the vehicle stops. In this way, when sudden braking is requested, torque fluctuations of the axles and drive axles can be suppressed according to the time waveform until the vehicle stops.

[0010] In addition, in the vehicle control device disclosed herein, a stopping timing for the vehicle to stop is predicted based on the time waveform of the wheel speed, and when the fluctuation range of the wheel speed reaches a predetermined low fluctuation state during execution of the reduction control, execution of the reduction control is terminated and the braking force applying device is controlled so that the vehicle stops at the predicted stopping timing. This makes it possible to stop the vehicle at the predicted stopping timing and suppress an increase in braking distance.

[0011] Furthermore, in the vehicle control device disclosed herein, the reduction control may control the braking force application device so that the braking force applied from the braking force application device is reduced once for every two fluctuations in the wheel speed in the predicted time waveform of the wheel speed. In this way, torque fluctuations in the axles and drive shafts can be suppressed while maintaining a certain level of braking force applied to the wheels.

[0012] In the vehicle control device of the present disclosure, a model of the time waveform of the wheel speed when the braking request is made while traveling on the undulating road may be generated by machine learning, and when a braking request is made while traveling on the undulating road, the time waveform of the wheel speed may be predicted using the model. By predicting the time waveform of the wheel speed using the model generated by machine learning, the accuracy of the prediction of the time waveform of the wheel speed is improved. Since the reduction control is performed using the time waveform of the wheel speed that is accurately predicted, it is possible to more appropriately suppress torque fluctuations of the axles and drive axles and to decelerate the vehicle. [Brief description of the drawings]

[0013] [Figure 1] 1 is a diagram showing an outline of the configuration of an electric vehicle 20 equipped with a vehicle control device according to an embodiment of the present invention. [Diagram 2] FIG. 1 is an explanatory diagram showing an example of how a machine learning model M1 is created by machine learning. [Diagram 3] FIG. 1 is an explanatory diagram showing an example of how a machine learning model M2 is created by machine learning. [Figure 4]1 is a flowchart showing an example of a brake control routine executed by the electronic control unit 40. [Diagram 5] 4 is a flowchart showing an example of a prediction processing routine executed by an electronic control unit 40. [Figure 6] FIG. 4 is an explanatory diagram showing an example of changes over time in brake oil pressure Pboil and wheel speed Vw. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] An embodiment of the present disclosure will be described with reference to the drawings. Fig. 1 is a schematic diagram showing the configuration of an electric vehicle 20 equipped with a vehicle control device according to an embodiment of the present invention. As shown in the figure, the electric vehicle 20 of the embodiment includes a motor 22, an inverter 24, a battery 30, a system main relay 34, an electronic control unit 40, and a brake actuator (braking force application device) 62.

[0015] The motor 22 is configured as a synchronous generator motor, and includes a rotor in which a permanent magnet is embedded and a stator around which a three-phase coil is wound. The rotor of the motor 22 is connected to a drive shaft 26 that is connected to drive wheels 28a, 28b via a differential gear 27.

[0016] The inverter 24 is connected to the motor 22 and also to the power line 32. The inverter 24 is configured as a well-known inverter circuit having six transistors and six diodes.

[0017] The battery 30 is configured as, for example, a lithium ion secondary battery or a nickel-hydrogen secondary battery, and is connected to a power line 32. A system main relay 34 is attached to the power line 32. Although not shown, the system main relay 34 has a positive relay provided on a positive bus bar of the power line 32, a negative relay provided on a negative bus bar of the power line 32, and a precharge circuit in which a precharge resistor and a precharge relay are connected in series to bypass the negative relay. A smoothing capacitor 36 and auxiliary equipment (not shown) are also connected to the power line 32.

[0018] The electronic control unit 40 is configured as a microprocessor centered around a CPU 42, and in addition to the CPU 42, includes a ROM 44 for storing processing programs, a RAM 46 for temporarily storing data, a flash memory (not shown), an input / output port (not shown), a communication port (not shown), etc.

[0019] Signals from various sensors are input to the electronic control unit 40 via input ports. Examples of signals input to the electronic control unit 40 include a rotational position θm from a rotational position detection sensor (e.g., resolver) 22a that detects the rotational position of the rotor of the motor 22, a voltage VB from a voltage sensor 31a attached between the terminals of the battery 30, and a current IB from a current sensor 31b attached to the output terminal of the battery 30. Also included is a voltage Vin of the capacitor 36 (power line 32) from a voltage sensor 37 attached between the terminals of the capacitor 36. Further examples include a start signal from a start switch 50, a shift position SP from a shift position sensor 52 that detects the operation position of the shift lever 51, an accelerator opening from an accelerator pedal position sensor 54 that detects the amount of depression of an accelerator pedal 53, a brake pedal position from a brake pedal position sensor 56 that detects the amount of depression of a brake pedal 55, a vehicle speed V from a vehicle speed sensor 58, and a three-axis acceleration α from a three-axis acceleration sensor 59 that detects acceleration in the horizontal, longitudinal, and vertical directions.

[0020] Various control signals are output via an output port from the electronic control unit 40. Examples of signals output from the electronic control unit 40 include a switching control signal to the transistor of the inverter 24, a drive control signal to the system main relay 34, and the like.

[0021] The electronic control unit 40 calculates the rotation speed Nm of the motor 22 based on the rotation position θm from the rotation position detection sensor 22a, and calculates the motor torque Tm as the torque output from the motor 22 based on the current flowing through the three-phase coil of the motor 22 detected by a current sensor (not shown). The electronic control unit 40 calculates the pitch angle θp based on the three-axis acceleration α from the three-axis acceleration sensor 59. The electronic control unit 40 calculates the tire ground load Lv and the front-rear load Ll based on the vehicle weight, the length of the wheelbase, the height of the center of gravity, the acceleration in the vehicle's traveling direction, etc.

[0022] The brake actuator 62 is configured to adjust the hydraulic pressure of the pistons of the disc brakes 66a to 66d so that a braking force corresponding to the brake share in the braking force applied to the vehicle according to the pressure (brake hydraulic pressure) Pboil of the brake master cylinder 60 generated in response to depression of the brake pedal 55 and the vehicle speed V acts on the driven wheels 29a, 29b and the driving wheels 28a, 28b, and to adjust the hydraulic pressure of the pistons of the disc brakes 66a to 66d so that a braking force acts on the driven wheels 29a, 29b and the driving wheels 28a, 28b regardless of depression of the brake pedal 55. The brake hydraulic pressure Pboil is detected by a hydraulic sensor (not shown) that detects the pressure (brake hydraulic pressure) of the brake master cylinder 60. Hereinafter, the braking force applied to the driven wheels 29a, 29b and the driving wheels 28a, 28b by the operation of the brake actuator 62 may be referred to as a hydraulic brake. The brake actuator 62 is controlled by a brake electronic control unit (hereinafter referred to as a brake ECU) 64. The brake ECU 64 communicates with the electronic control unit 40, and drives and controls the brake actuator 62 based on control signals from the electronic control unit 40, and outputs data regarding the state of the brake actuator 62, such as the brake hydraulic pressure Pboil, to the electronic control unit 40 as necessary.

[0023] The brake ECU 64 receives inputs of wheel speeds Vdr, Vdl, Vnr, Vnl from wheel speed sensors 68a-68d attached to the driven wheels 29a, 29b and the driving wheels 28a, 28b, brake pad temperatures Tbpa-Tbpd from temperature sensors 69a-69d that detect the temperatures of the brake pads of the disc brakes 66a-66d, and a steering angle from a steering angle sensor not shown.

[0024] The brake ECU 64 calculates the braking torque to be applied to the driving wheels 28a, 28b and the driven wheels 29a, 29b according to the depression amount of the brake pedal 55 when the driver depresses the brake pedal 55. The brake ECU 64 then divides the braking torque to be applied to the driving wheels 28a, 28b and the driven wheels 29a, 29b into the braking torque by the disc brakes 66a-66d and the braking torque by the regenerative control of the motor 22. The brake ECU 64 controls the driving of the brake actuator 62 so that the braking torque (required braking force) Tb* to be applied from the disc brakes 66a-66d is applied. The braking torque Tbm* by the regenerative control of the motor 22 is transmitted to the electronic control unit 40, and the electronic control unit 40 that receives it controls the switching of the switching elements of the inverter 24 so that the braking torque to be output to the motor 22 is output.

[0025] Furthermore, the brake ECU 64 inputs the wheel speeds Vdr, Vdl, Vnr, and Vnl from the wheel speed sensors 68a to 68d at predetermined time intervals (e.g., every few msec), and calculates the variation amounts ΔVdr, ΔVdl, ΔVnr, and ΔVnl from the wheel speeds Vdr, Vdl, Vnr, and Vnl from the previous input, and the integrated value Sdv of the average value (=(ΔVdr+ΔVdl+ΔVnr+ΔVnl) / 4) of the variation amounts ΔVdr, ΔVdl, ΔVnr, and ΔVnl. Then, when the integrated value Sdv becomes equal to or greater than a threshold value Sdref1, it is determined that the road surface is an undulating road, and the undulating road flag F is set to a value of 1. When the integrated value Sdv becomes less than the threshold value Sdref1, it is determined that the road surface is not an undulating road, and the undulating road flag F is set to a value of 0.

[0026] Next, the operation of the electric vehicle 20 of the embodiment configured as described above, particularly the operation when a driving request is made while the electric vehicle 20 is traveling on an undulating road, will be described. First, machine learning performed in advance in the electric vehicle 20 (for example, by driving the electric vehicle 20 on a test course or a chassis dynamometer before the electric vehicle 20 is shipped) will be described, and then the operation during traveling will be described.

[0027] 2 is an explanatory diagram showing an example of a state in which a machine learning model M1 is created by machine learning. In the electric vehicle 20 of the embodiment, the electronic control unit 40 creates a machine learning model M1 in advance by machine learning, using the motor torque Tm, the vehicle speed V, the wheel speeds Vdr, Vdl, Vnr, and Vnl, the ground load Lv, and the pitch angle θp as input data, and the friction coefficient μ (tire μ) between the tire and the road surface as output data, and stores the model in the ROM 44 of the electronic control unit 40. Here, the vehicle speed V is detected by the vehicle speed sensor 58, and the wheel speeds Vdr, Vdl, Vnr, and Vnl are detected by the wheel speed sensors 68a to 68d. The motor torque Tm, the ground load Lv, and the pitch angle θp are calculated by the electronic control unit 40. The tire μ is calculated in advance as the friction coefficient between the tire and the road surface of the test course or the ground surface of the chassis dynamometer.

[0028] 3 is an explanatory diagram showing an example of how the machine learning model M2 is created by machine learning. In the electric vehicle 20 of the embodiment, the electronic control unit 40 creates a machine learning model M2 in advance by machine learning, in which the tire μ, motor torque Tm, rotation speed Nm, vehicle speed V, wheel speeds Vdr, Vdl, Vnr, Vnl, ground load Lv, front-rear load Ll, pitch angle θp, brake oil pressure Pboil, and brake pad temperature Tbpa to Tbpd when a request for sudden braking is made and braking torque is applied to the driving wheels 28a, 28b and the driven wheels 29a, 29b are used as input data, and the machine learning model M2 is generated in which the time waveform of the average value of the wheel speeds Vdr, Vdl, Vnr, Vnl (hereinafter referred to as "wheel speed Vw") during the period from when a predetermined sudden braking is made to when the electric vehicle 20 stops is used as output data, and stores the model in the ROM 44 of the electronic control unit 40. Here, the vehicle speed V is detected by the vehicle speed sensor 58, and the wheel speeds Vdr, Vdl, Vnr, and Vnl are detected by the wheel speed sensors 68a to 68d. The brake oil pressure Pboil is detected by an oil pressure sensor (not shown), and the brake pad temperatures Tbpa to Tbpd are detected by temperature sensors 60a to 69d, which are input via the brake ECU 64. The motor torque Tm, the rotation speed Nm, the ground load Lv, the front and rear load Ll, and the pitch angle θp are calculated by the electronic control unit 40. The tire μ is calculated in advance as the friction coefficient between the road surface of the test course or the ground surface of the chassis dynamometer and the tire. The sudden braking request can be, for example, when the gradient Kpboil of the brake oil pressure Pboil with respect to the amount of change over time exceeds a predetermined value dpref.

[0029] Next, a description will be given of the operation of the electric vehicle 20 of the embodiment when the electric vehicle 20 is traveling on an undulating road. Fig. 4 is a flowchart showing an example of a brake control routine executed by the electronic control unit 40. This routine is executed while the electric vehicle 20 is traveling.

[0030] When this routine is executed, the CPU 42 of the electronic control unit 40 executes a process of inputting the wheel speeds Vdr, Vdl, Vnr, and Vnl, the brake hydraulic pressure Pboil, and the undulating road flag F (step S100). The wheel speeds Vdr, Vdl, Vnr, and Vnl detected by the wheel speed sensors 68a to 68d are input. The brake hydraulic pressure Pboil detected by a hydraulic pressure sensor (not shown) is input via the brake ECU 64.

[0031] After inputting the data necessary for processing including the predicted tire μ, it is determined whether the undulating road flag F has a value of 1 (step S110). If the undulating road flag F has a value of 0, it is determined that the vehicle is not traveling on an undulating road, and this routine is terminated.

[0032] When the undulating road flag F is set to a value of 1 in step S110, the slope Kpboil of the brake oil pressure Pboil with respect to time is calculated using the following equation (1) (step S120). In equation (1), "previous Pboil" is the brake oil pressure Pboil input the previous time step S100 or step S140 was executed. Time tref is the elapsed time since the previous time step S100 or step S140 was executed.

[0033] Kpboil = (Pboil - previous Pboil) / tref (1)

[0034] Next, it is determined whether the slope Kpboil exceeds a threshold value Kref (step S130). The threshold value Kref is a threshold value for determining whether the brake hydraulic pressure Pboil has changed suddenly in a short time. The brake hydraulic pressure Pboil is generated in response to depression of the brake pedal 55. Therefore, step S130 is a process for determining whether the brake pedal 55 has been depressed suddenly in a short time, that is, whether sudden braking has been requested. If the slope Kpboil does not exceed the threshold value Kref, this routine is terminated.

[0035] When the inclination Kpboil exceeds the threshold value Kref in step S130, it is determined that sudden braking is required, and a process is executed to input the motor torque Tm, the rotation speed Nm, the vehicle speed V, the wheel speeds Vdr, Vdl, Vnr, Vnl, the ground load Lv, the front-rear load Ll, the pitch angle θp, the brake oil pressure Pboil, the brake pad temperatures Tbpa to Tbpd, and the tire μ (step S140). The vehicle speed V is detected by the vehicle speed sensor 58, and the wheel speeds Vdr, Vdl, Vnr, Vnl are detected by the wheel speed sensors 68a to 68d. The brake oil pressure Pboil is detected by a hydraulic sensor (not shown), and the brake pad temperatures Tbpa to Tbpd are detected by the temperature sensors 60a to 69d, and are input via the brake ECU 64. The motor torque Tm, the rotation speed Nm, the ground load Lv, the front-rear load Ll, and the pitch angle θp are calculated by the electronic control unit 40. The tire μ is predicted using the machine learning model M1 and input from the RAM 46.

[0036] Here, prediction of tire μ will be described. Fig. 5 is a flow chart showing an example of a prediction processing routine executed by the electronic control unit 40. This routine is repeatedly executed during traveling.

[0037] When this routine is executed, the CPU 42 of the electronic control unit 40 inputs the motor torque Tm, the vehicle speed V, the wheel speeds Vdr, Vdl, Vnr, Vnl, the ground load Lv, the pitch angle θp, and the undulating road flag F (step S300). The vehicle speed V is inputted as detected by the vehicle speed sensor 58, and the wheel speeds Vdr, Vdl, Vnr, Vnl are inputted as detected by the wheel speed sensors 68a to 68d. The motor torque Tm, the ground load Lv, and the pitch angle θp are inputted as calculated by the electronic control unit 40. As described above, the undulating road flag F is inputted as set based on the wheel speeds Vdr, Vdl, Vnr, Vnl from the wheel speed sensors 68a to 68d.

[0038] Next, the motor torque Tm, the vehicle speed V, the wheel speeds Vdr, Vdl, Vnr, Vnl, the ground load Lv, and the pitch angle θp are used as input data to predict tire μ using the machine learning model M1 (step S310), and it is determined whether the undulating road flag F has a value of 1 (step S320). If the undulating road flag F is not a value of 1, this routine is terminated, and if the undulating road flag F has a value of 1, the predicted tire μ is stored in the RAM 46 (step S330), and this routine is terminated.

[0039] Next, the data input in step S140, i.e., the tire μ, motor torque Tm, rotation speed Nm, vehicle speed V, wheel speeds Vdr, Vdl, Vnr, Vnl, ground load Lv, front-rear load Ll, pitch angle θp, brake oil pressure Pboil, and brake pad temperatures Tbpa to Tbpd, are used as input data to predict the time waveform of the wheel speed Vw from the current time until the electric vehicle 20 stops (step S150) using the machine learning model M2. FIG. 6 is an explanatory diagram showing an example of the time change of the brake oil pressure Pboil and the wheel speed Vw. Time t0 is the timing at which it is determined in step S130 that the slope Kpboil exceeds the threshold value Kref. Time t1 is the timing at which the vehicle stops. In step S150, a process is performed to predict the time change (time waveform) of the wheel speed Vw from time t0 to time t1 in FIG. 6. As the vehicle is now traveling on an undulating road, the vehicle bounces on the undulating road, causing the drive wheels 28a, 28b and the driven wheels 29a, 29 to spin freely. When the vehicle touches the ground, the rotation speed of the drive wheels 28a, 28b and the driven wheels 29a, 29 decreases, causing the wheel speed Vw to fluctuate (increase or decrease) periodically.

[0040] Then, reduction control is executed to adjust the brake hydraulic pressure by controlling the brake actuator 62 so that a braking torque reduced from the braking torque Tb* to be applied from the disc brakes 66a-66d to the driving wheels 28a, 28b and the driven wheels 29a, 29b acts on the driving wheels 28a, 28b and the driven wheels 29a, 29b at a timing in accordance with the variation of the wheel speed Vw in the time waveform of the wheel speed Vw, once every two variations of the wheel speed Vw (step S160). By such control, as shown in Fig. 6, the brake hydraulic pressure Pboil is reduced from the brake hydraulic pressure Pbo* corresponding to the braking torque Tb* at a timing when the wheel speed Vw decreases, and returns to the brake hydraulic pressure Pbo* at a timing when the wheel speed Vw increases, once every two variations of the wheel speed Vw. This makes it possible to suppress torque fluctuations in the axles and drive shafts 26, compared to applying a constant braking torque Tb* that does not change over time from the disc brakes 66a-66d to the drive wheels 28a, 28b and the driven wheels 29a, 29b regardless of fluctuations in the wheel speed Vw. Also, it is possible to decelerate the vehicle more quickly, compared to applying a braking torque smaller than the constant braking torque Tb* from the disc brakes 66a-66d to the drive wheels 28a, 28b and the driven wheels 29a, 29b regardless of fluctuations in the wheel speed Vw. Therefore, it is possible to suppress torque fluctuations in the axles and drive shafts 26, and to decelerate the vehicle more appropriately.

[0041] Next, the wheel speeds Vdr, Vdl, Vnr, and Vnl are input (step S170) in the same manner as in steps S100 and S140, and an integrated value Sdv of the fluctuation amounts ΔVdr, ΔVdl, ΔVnr, and ΔVnl from the wheel speeds Vdr, Vdl, Vnr, and Vnl input in the previously executed steps S100 and S140 and the average value (=(ΔVdr+ΔVdl+ΔVnr+ΔVnl) / 4) of the fluctuation amounts ΔVdr, ΔVdl, ΔVnr, and ΔVnl is calculated (step S180), and it is determined whether the integrated value Sdv is less than a threshold value Sdref2 (step S190). The threshold value Sdref2 is a threshold value for determining whether the fluctuation range of the wheel speed Vw is in a predetermined low fluctuation state that can be considered to be sufficiently low. When the integrated value Sdv is equal to or greater than the threshold value Sdref2, it is determined that the fluctuation range of the wheel speed Vw has not become sufficiently small, and the process returns to step S140. Steps S140 to S190 are repeated until the integrated value Sdv becomes less than the threshold value Sdref2.

[0042] Then, when the integrated value Sdv becomes less than the threshold value Sdref2, stopping control is executed to control the brake actuator 62 so that the vehicle stops at time t1 when the electric vehicle 20 stops in the waveform of the wheel speed Vw predicted in step S150 (step S200), the vehicle speed V is input in the same manner as in step S140 (step S210), and it is determined whether the vehicle speed V has a value of 0 (step S220). When the vehicle speed V is not a value of 0, that is, when the electric vehicle 20 is not stopped, steps S200 to S220 are repeated until the electric vehicle 20 stops. Then, when the electric vehicle 20 stops, this routine is terminated. As a result, the electric vehicle 20 can be stopped at time t1, which is the predicted stopping timing, and an increase in the braking distance can be suppressed.

[0043] According to the electric vehicle 20 equipped with the vehicle control device of the present embodiment described above, when a braking request is made while traveling on an undulating road, the machine learning model M2 is used to predict the time waveform of the wheel speed Vw from the current time until the electric vehicle 20 is stopped, and reduction control is performed to adjust the brake hydraulic pressure by controlling the brake actuator 62 so that a braking torque reduced from the braking torque Tb* that should be applied to the drive wheels 28a, 28b and the driven wheels 29a, 29b from the disc brakes 66a-66d is applied to the drive wheels 28a, 28b and the driven wheels 29a, 29b in accordance with a timing that matches the fluctuation of the wheel speed Vw in the time waveform of the wheel speed Vw, thereby suppressing torque fluctuations in the axles and drive axles 26 and more appropriately decelerating the electric vehicle 20.

[0044] In addition, the time t1 at which the electric vehicle 20 will stop (stopping timing) is predicted based on the time waveform of the wheel speed Vw, and when the integrated value Sdv becomes less than the threshold value Sdref2 during execution of the reduction control, the execution of the reduction control is terminated and stopping control is executed to control the brake actuator 62 so that the vehicle stops at time t0. Therefore, the vehicle can be stopped at time t1, which is the predicted stopping timing, and an increase in braking distance can be suppressed.

[0045] Furthermore, in the reduction control, the brake actuator 62 is controlled to adjust the brake hydraulic pressure so that a braking torque reduced from the braking torque Tb* that should be applied to the driving wheels 28a, 28b and the driven wheels 29a, 29b from the disc brakes 66a-66d is applied to the driving wheels 28a, 28b and the driven wheels 29a, 29b once for every two fluctuations in the wheel speed Vw, so that torque fluctuations in the axles and drive axle 26 can be suppressed while maintaining a certain level of braking force applied to the driving wheels 28a, 28b and the driven wheels 29a, 29b.

[0046] Then, a machine learning model M2 is generated by machine learning as a model of the time waveform of the wheel speed Vw when a braking request is made while traveling on an undulating road, and when a braking request is made while traveling on an undulating road, the machine learning model M2 is used to predict the time waveform of the wheel speed Vw, so that torque fluctuations in the axles and drive shafts 26 can be more appropriately suppressed and the electric vehicle 20 can be decelerated.

[0047] In the above-described embodiment, in the reduction control, a braking torque reduced from the braking torque Tb* to be applied from the disc brakes 66a-66d to the driving wheels 28a, 28b and the driven wheels 29a, 29b is applied to the driving wheels 28a, 28b and the driven wheels 29a, 29b once every two fluctuations of the wheel speed Vw. However, a braking torque reduced from the braking torque Tb* to be applied from the disc brakes 66a-66d to the driving wheels 28a, 28b and the driven wheels 29a, 29b may be applied to the driving wheels 28a, 28b and the driven wheels 29a, 29b once every three fluctuations of the wheel speed Vw or once every four fluctuations of the wheel speed Vw.

[0048] In the above embodiment, the braking request is a request for sudden braking. However, the braking request may be a braking request that is lower than the sudden braking.

[0049] In the above embodiment, the machine learning model M2 is generated as a model of the time waveform of the wheel speed Vw when a braking request is made while traveling on an undulating road by machine learning, and when a braking request is made while traveling on an undulating road, the machine learning model M2 is used to predict the time waveform of the wheel speed Vw. However, the time waveform of the wheel speed Vw may be predicted by a method other than machine learning.

[0050] The correspondence between the main elements of the embodiment and the main elements of the invention described in the section on means for solving the problems will be described. In the embodiment, the electronic control unit 40 and the brake ECU 64 correspond to the "vehicle control device."

[0051] Note that the correspondence between the main elements of the embodiment and the main elements of the invention described in the Means for Solving the Problem column does not limit the elements of the invention described in the Means for Solving the Problem column, since the embodiment is an example for specifically explaining the form for implementing the invention described in the Means for Solving the Problem column. In other words, the interpretation of the invention described in the Means for Solving the Problem column should be made based on the description in that column, and the embodiment is merely a specific example of the invention described in the Means for Solving the Problem column.

[0052] The above describes embodiments for implementing the present disclosure, but the present disclosure is not limited to these embodiments, and it goes without saying that the present disclosure can be implemented in various forms without departing from the gist of the present disclosure. [Industrial Applicability]

[0053] The present disclosure is applicable to the vehicle control device manufacturing industry and the like. [Explanation of symbols]

[0054] 20 electric vehicle, 22 motor, 22a rotational position detection sensor, 24 inverter, 26 drive shaft, 27 differential gear, 28a, 28b drive wheels, 29a, 29b driven wheels, 30 battery, 31a voltage sensor, 31b current sensor, 32 power line, 34 system main relay, 36 capacitor, 37 voltage sensor, 38 auxiliary equipment, 40 electronic control unit, 42 CPU, 44 ROM, 46 RAM, 50 start switch, 51 shift lever, 52 shift lever position sensor, 53 accelerator pedal, 54 accelerator pedal position sensor, 55 brake pedal, 56 brake pedal position sensor, 58 vehicle speed sensor, 59 three-axis acceleration sensor, 60 brake master cylinder, 62 brake actuator, 64 brake electronic control unit, 66a to 66d disc brake, 68a to 68d Wheel speed sensors, 69a-69d temperature sensors.

Claims

1. A vehicle control device is used in a vehicle including a motor that outputs power to a drive shaft and a braking force application device that applies a braking force to a wheel connected to the drive shaft via an axle, the vehicle control device controlling the motor and the braking force application device, When a braking request is made while traveling on an undulating road, a time waveform of a wheel speed when a requested braking force based on the braking request is applied is predicted, and reduction control is performed to control the braking force application device so that a braking force reduced from the requested braking force is applied from the braking force application device in accordance with a timing of fluctuation of the wheel speed in the predicted time waveform of the wheel speed. Vehicle control device.

2. The vehicle control device according to claim 1, the braking request is a request for sudden braking, As the time waveform of the wheel speed, a time waveform until the vehicle stops is predicted. Vehicle control device.

3. The vehicle control device according to claim 2, predicting a timing at which the vehicle will stop based on a time waveform of the wheel speed; When the fluctuation range of the wheel speed reaches a predetermined low fluctuation state during the execution of the reduction control, the execution of the reduction control is terminated, and the braking force application device is controlled so that the vehicle stops at the predicted stopping timing. Vehicle control device.

4. The vehicle control device according to claim 1, The reduction control controls the braking force application device so that the braking force applied from the braking force application device is reduced once for every two fluctuations in the wheel speed in the predicted time waveform of the wheel speed. Vehicle control device.

5. The vehicle control device according to claim 1, generating a model of a time waveform of the wheel speed when the braking request is made while the vehicle is traveling on the undulating road by machine learning; When the braking request is made while the vehicle is traveling on the undulating road, the model is used to predict the time waveform of the wheel speed. Vehicle control device.

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