JP6475012B2 - Vehicle control apparatus and vehicle control method - Google Patents

Description

  The present invention relates to a vehicle control device and a vehicle control method.

  Conventionally, for example, in Patent Document 1 below, drive control using a yaw rate sensor value as a yaw rate F / B value in an electric vehicle that can perform left and right independent drive and performs running stability control that controls a moment around the center of gravity with a yaw rate. An apparatus is disclosed.

JP-A-10-271613

  However, the detected value of the yaw rate sensor that detects the yaw rate generated by the vehicle includes a noise component. In the technique described in Patent Document 1, the noise component of the detection value of the yaw rate sensor affects the feedback control, and there arises a problem that the drive of the motor to be controlled vibrates due to the noise.

  On the other hand, when the low-pass filter process is performed on the actual yaw rate, there is a problem that the phase of the signal after the filter process is delayed as a price for suppressing the noise. For this reason, depending on the filter processing, the yaw rate after the filter processing becomes a yaw rate deviating from the original behavior of the actual vehicle. When the phase of the yaw rate to be fed back is delayed, the yaw rate as an object to be compensated at the time of steering increases. In this case, for example, if it is attempted to compensate the yaw rate by torque vectoring of the rear wheels, there is a problem that a required value such as a motor torque for driving the rear wheels increases and the turning support amount becomes excessive. Therefore, when the actual yaw rate is processed with a filter that prioritizes noise removal performance, there is a problem that vehicle behavior tends to become unstable.

  Accordingly, the present invention has been made in view of the above problems, and an object of the present invention is to feed back the deviation between the target yaw rate of the vehicle and the actual yaw rate actually generated by the vehicle. It is an object of the present invention to provide a new and improved vehicle behavior control apparatus and vehicle behavior control method capable of reliably suppressing the influence of sensor noise and improving drivability.

In order to solve the above problems, according to an aspect of the present invention, a target yaw rate acquisition unit that acquires a target yaw rate of a vehicle based on a steering angle and a vehicle speed, and a yaw rate model value that calculates a yaw rate model value from a vehicle model By changing the distribution ratio between the yaw rate model value and the sensor value based on the difference between the calculation unit, the yaw rate sensor that detects the actual yaw rate of the vehicle, and the sensor value detected by the yaw rate model value and the yaw rate sensor The yaw rate model value and the sensor value are distributed, a feedback yaw rate calculation unit that calculates a feedback yaw rate from the yaw rate model value and the sensor value, and a vehicle turns based on a difference between the target yaw rate and the feedback yaw rate. A vehicle turning control unit for controlling the vehicle Your device is provided.

  The feedback yaw rate calculation unit may calculate the feedback yaw rate by making the distribution of the yaw rate model value larger than the sensor value as the difference between the yaw rate model value and the sensor value is smaller.

  Further, the feedback yaw rate calculation unit may calculate the feedback yaw rate by increasing the distribution of the sensor value to be larger than the yaw rate model value as the difference between the yaw rate model value and the sensor value is larger. .

  The vehicle turning control unit may individually control a motor that drives each of the left and right wheels based on a difference between the target yaw rate and the feedback yaw rate.

  Further, the vehicle turning control includes: a rotation speed difference acquisition unit that acquires a rotation speed difference between left and right wheels; and a gain calculation unit that calculates a gain according to a friction coefficient of a road surface based on the rotation speed difference. The unit may individually control the motor that drives each of the left and right wheels based on a difference between the target yaw rate and the feedback yaw rate and the gain.

  The rotational speed difference acquisition unit obtains a first rotational speed difference between the left and right wheels obtained from the vehicle model and a second rotational speed difference obtained from the rotational speed difference between the motors that drive the left and right wheels, respectively. Obtaining and calculating the difference between the rotation speeds of the left and right wheels based on the difference between the first rotation speed difference and the second rotation speed difference.

  The vehicle turning control unit may individually control the motors that drive the left and right wheels so that the feedback yaw rate becomes the target yaw rate.

Further, the feedback yaw rate calculation unit may be one of allocating the sensor value and the yaw rate model value using the weighted gain set in accordance with the difference between the sensor value and the yaw rate model values.

Further, the vehicle turning control unit calculates a moment to be added to the vehicle body based on a difference between the target yaw rate and the feedback yaw rate,
A correction unit for correcting the moment based on the gain;
A motor required torque calculation unit that calculates a torque instruction value of the motor that drives each of the left and right wheels based on the corrected moment.

In order to solve the above problem, according to another aspect of the present invention, a step of obtaining a target yaw rate of the vehicle based on a steering angle and a vehicle speed, a step of calculating a yaw rate model value from the vehicle model, Detecting the actual yaw rate of the vehicle with a yaw rate sensor, and changing the distribution ratio between the yaw rate model value and the sensor value based on the difference between the yaw rate model value and the sensor value detected by the yaw rate sensor, Allocating a model value and the sensor value, calculating a feedback yaw rate from the yaw rate model value and the sensor value, and controlling turning of the vehicle based on a difference between the target yaw rate and the feedback yaw rate; A method for controlling a vehicle is provided.

  As described above, according to the present invention, when the vehicle is controlled by feeding back the deviation between the target yaw rate of the vehicle and the actual yaw rate actually generated by the vehicle, the influence of sensor noise is reliably suppressed. It becomes possible to improve drivability.

It is a mimetic diagram showing a vehicle concerning one embodiment of the present invention. It is a schematic diagram for demonstrating general yaw rate feedback control. It is a characteristic view which shows the case where a filter process is performed (broken line) and the case where a filter process is not performed (solid line) regarding the characteristic of the actual yaw rate γ detected by the yaw rate sensor. FIG. 6 is a characteristic diagram illustrating a case where a filter process is performed (broken line) and a case where a filter process is not performed (solid line) for a difference Δγ between a target yaw rate and an actual yaw rate γ. FIG. 5 is a characteristic diagram illustrating a case where a filter process is performed (broken line) and a case where a filter process is not performed (solid line) for the rear wheel motor torque instruction value TvTrq calculated based on the difference Δγ illustrated in FIG. 4. FIG. 2 is a schematic diagram showing in detail a configuration of a control device according to the present embodiment and its periphery. It is a schematic diagram which shows the gain map at the time of the weighting gain calculation part calculating the weighting gain a. It is a characteristic view which shows the dynamic characteristic of a tire. It is a flowchart which shows the process in which the low micro judgment output gain calculation part calculates the low micro output gain micro. It is a flowchart which shows the whole process of this embodiment. It is a flowchart which shows the process of step S122 of FIG. It is a flowchart which shows the process in which a vehicle yaw rate calculation part calculates yaw rate model value (gamma) _clc. It is a flowchart which shows the process which calculates additional torque Tvmot. For comparison with the present embodiment, it is a characteristic diagram showing a case where control is performed using the actual yaw rate γ_sens detected by the yaw rate sensor as the feedback yaw rate γ_F / B. In the example shown in FIG. 14, the actual yaw rate γ_sens detected by the yaw rate sensor, the target yaw rate γ_Tgt, the difference Δγ between the target yaw rate γ_Tgt and the actual yaw rate γ_sens, and the yaw rate model value γ_clc are shown. It is a characteristic view showing a case where feedback control to the target yaw rate γ_Tgt is performed using the yaw rate model value γ_clc instead of the actual yaw rate γ_sens detected by the yaw rate sensor. FIG. 9 is a characteristic diagram showing control according to the present embodiment and showing a case where an actual yaw rate γ_sens detected by a yaw rate sensor 142 and a yaw rate model value γ_clc are divided by a weighting coefficient to obtain a feedback yaw rate γ_F / B. It is a characteristic view which shows the case where it carries out slalom driving | running | working on the low μ road surface (snowy road etc.), Comprising: It is a characteristic view which shows the case where control using the low μ output gain μG according to this embodiment is not performed. It is a characteristic view which shows the case where it carries out slalom driving | running | working on the low μ road surface (snowy road etc.), Comprising: It is a characteristic view which shows the case where control using the low μ output gain μG according to this embodiment is not performed. It is a characteristic view which shows the case where it carries out slalom driving | running | working on the low μ road surface (snowy road etc.), Comprising: It is a characteristic view which shows the case where control using the low μ output gain μG according to this embodiment is not performed. It is a characteristic view which shows the control which concerns on this embodiment, Comprising: It is a characteristic view which shows the case where slalom driving | running | working is performed similarly to FIGS. It is a characteristic view which shows the control which concerns on this embodiment, Comprising: It is a characteristic view which shows the case where slalom driving | running | working is performed similarly to FIGS. It is a characteristic view which shows the control which concerns on this embodiment, Comprising: It is a characteristic view which shows the case where slalom driving | running | working is performed similarly to FIGS.

  Exemplary embodiments of the present invention will be described below in detail with reference to the accompanying drawings. In addition, in this specification and drawing, about the component which has the substantially same function structure, duplication description is abbreviate | omitted by attaching | subjecting the same code | symbol.

  First, with reference to FIG. 1, the structure of the vehicle 1000 which concerns on one Embodiment of this invention is demonstrated. FIG. 1 is a schematic diagram showing a vehicle 1000 according to the present embodiment. As shown in FIG. 1, a vehicle 1000 includes driving force generators (motors) 108, 110, 112, driving front wheels 100 and 102, rear wheels 104 and 106, front wheels 100 and 102, and rear wheels 104 and 106. 114, the gear boxes 116, 118, 120, 122 and the motors 108, 110, 112, 114 that transmit the driving force of the motors 108, 110, 112, 114 to the front wheels 100, 102 and the rear wheels 104, 106, respectively. Inverters 123, 124, 125, 126 to be controlled, wheel speed sensors 127, 128 for detecting the respective wheel speeds (vehicle speed V) of the rear wheels 104, 106, a steering wheel 130 for steering the front wheels 100, 102, a longitudinal acceleration sensor 132, lateral acceleration sensor 134, battery 136, rudder angle sensor 138, parameter Steering mechanism 140, a yaw rate sensor 142, an inhibitor position sensor (IHN) 144, it is configured to include an accelerator opening degree sensor 146, the control unit (controller) 200.

  The vehicle 1000 according to the present embodiment is provided with motors 108, 110, 112, and 114 for driving the front wheels 100 and 102 and the rear wheels 104 and 106, respectively. Therefore, the driving torque can be controlled by each of the front wheels 100 and 102 and the rear wheels 104 and 106. Accordingly, the yaw rate can be generated by the torque vectoring control by driving each of the front wheels 100 and 102 and the rear wheels 104 and 106 independently of the yaw rate generation by the steering of the front wheels 100 and 102. Steering steering assist can be performed. That is, in the vehicle 1000 according to the present embodiment, the turning control for assisting steering steering is performed by controlling the turning moment (hereinafter also referred to as yaw moment) by the vehicle body turning angular velocity (hereinafter referred to as yaw rate).

  The drive of each motor 108, 110, 112, 114 is controlled by controlling the inverters 123, 124, 125, 126 corresponding to the motors 108, 110, 112, 114 based on commands from the control device 200. The The driving force of each motor 108, 110, 112, 114 is transmitted to each of the front wheels 100, 102 and the rear wheels 104, 106 via the gear boxes 116, 118, 120, 122.

  The power steering mechanism 140 controls the steering angle of the front wheels 100 and 102 by torque control or angle control according to the operation of the steering wheel 130 by the driver. The steering angle sensor 138 detects the steering angle θh input by the driver operating the steering wheel 130. The yaw rate sensor 142 detects the actual yaw rate γ of the vehicle 1000. Wheel speed sensors 127 and 128 detect vehicle speed V of vehicle 1000.

  Note that the present embodiment is not limited to this form, and may be a vehicle in which only the rear wheels 104 and 106 independently generate a driving force. Further, the present invention can also be realized in a vehicle that does not include the external environment recognizing means 170 and performs only the steering control. Further, the present embodiment is not limited to torque vectoring based on driving force control, and can also be realized in a 4WS system for controlling the steering angle of the rear wheels.

  FIG. 2 is a schematic diagram for explaining general yaw rate feedback control. The target yaw rate γ_Tgt is obtained from the vehicle speed V and the steering angle θh. On the other hand, the actual yaw rate γ detected by the yaw rate sensor 142 is filtered, and the difference Δγ between the target yaw rate γ_Tgt and the filtered actual yaw rate γ is converted into the vehicle body additional moment Mg based on the vehicle specifications. Wheel motor torque instruction values (Frl (left rear wheel), Frr (right rear wheel)) are calculated. In this way, by feeding back the actual yaw rate γ to the target yaw rate γ_Tgt, the vehicle 1000 can be turned according to the target yaw rate γ_Tgt.

  Incidentally, when the yaw rate feedback control as shown in FIG. 2 is performed, if the control output increases due to the data delay by the filter, it becomes difficult to control the vehicle 1000 particularly in a region where the road resistance (road surface μ) is low. FIG. 3 shows the case where the filter process is performed (broken line) and the case where the filter process is not performed (solid line) regarding the characteristics of the actual yaw rate γ detected by the yaw rate sensor 142. As shown in FIG. 3, the absolute value of the actual yaw rate γ is smaller when the filter process is performed (broken line) than when the filter process is not performed (solid line). In particular, when the filter process is performed at a position where the actual yaw rate γ reaches the peak (dashed line), the absolute value of the actual yaw rate γ is remarkably small, and the filter process is performed when the filter process is performed (broken line). It can be seen that there is a large error from the absence (solid line).

  FIG. 4 shows the case where the filter process is performed (broken line) and the case where the filter process is not performed (solid line) for the difference Δγ between the target yaw rate γ_Tgt and the actual yaw rate γ. The target yaw rate γ_Tgt is the same in each case with or without filtering. For this reason, the smaller the actual yaw rate γ, the larger Δγ (feedback deviation). Accordingly, the absolute value of the difference Δγ between the target yaw rate γ_Tgt and the actual yaw rate γ is greater in the case where the filter process is performed (broken line) than in the case where the filter process is not performed (solid line). Since the control instruction value (motor torque instruction value) is obtained based on the difference Δγ, the control instruction value (motor torque instruction value) becomes larger when the filter process is performed.

  FIG. 5 shows a case where the filter process is performed (broken line) and a case where the filter process is not performed (solid line) for the wheel motor torque instruction value TvTrq calculated based on the difference Δγ shown in FIG. As is apparent from FIG. 5, when the filter process is performed (broken line), the motor torque instruction value is increased by ΔTrq as compared with the case where the filter process is not performed (solid line). For this reason, in the state where μ of the road surface is low, it causes a slip of the rear wheel.

  In general, yaw rate feedback control based on an actual yaw rate detected by a yaw rate sensor is applied to an anti-slip device (ESC). However, since the accuracy of the minimum value is not compensated, the influence of sensor noise can be avoided. Can not. Further, in a vehicle using a conventional engine, the detection value of the yaw rate sensor has been applied to an engine or a hydraulic brake system having a relatively responsive response, so that the influence of noise does not become a big problem.

  However, when trying to control the motor by the yaw rate feedback control, the influence of the noise of the yaw rate sensor is increased due to the high control responsiveness, which causes problems such as vibration of the motor. For this reason, it is necessary to perform a filtering process on the detection value of the yaw rate sensor. In this case, as described above, as a result of performing the filtering process, the control instruction value increases, and it may be difficult to control the vehicle.

  Therefore, in the present embodiment, the actual yaw rate γ detected by the yaw rate sensor 142 without performing the filtering process is used as it is, and the actual yaw rate γ and the yaw rate model value γ_clc obtained from the vehicle model are apportioned according to the reliability of the vehicle model. Thus, the feedback yaw rate γ_F / B is obtained. With this configuration, in this embodiment, the yaw rate of the vehicle body of the vehicle 1000 is controlled so that both turning assistance at extremely low speed and turning assistance at medium and high speeds are compatible, and the time delay is compensated for. It is possible to cope with the high response control without reducing the accuracy of the detection value 142. Details will be described below.

  FIG. 6 is a schematic diagram showing in detail the configuration of the control device 200 according to the present embodiment and its periphery. The control device 200 includes an in-vehicle sensor 202, a target yaw rate calculation unit 204, a vehicle yaw rate calculation unit (vehicle model) 206, a yaw rate F / B calculation unit 208, subtraction units 210, 212, 214, 216, a weighting gain calculation unit 218, a theory A left-right differential rotation calculation unit (vehicle model) 220, a vehicle body additional moment calculation unit 222, a low μ determination output gain calculation unit 224, a multiplication unit 226, and a motor required torque calculation unit 228 are configured.

  In FIG. 6, the in-vehicle sensor 202 includes the wheel speed sensors 127 and 128, the longitudinal acceleration sensor 132, the lateral acceleration sensor 134, the steering angle sensor 138, the yaw rate sensor 142, and the accelerator opening sensor 146 described above. The steering angle sensor 138 detects the steering angle θh of the steering wheel 130. The yaw rate sensor 142 detects the actual yaw rate γ of the vehicle 1000, and the wheel speed sensors 127 and 128 detect the vehicle speed V.

  The target yaw rate calculation unit 204 calculates the target yaw rate γ_tgt from the following equation (1) that represents a general two-wheel model. The target yaw rate γ_tgt corresponds to the vehicle yaw rate γ in the equation (1) of the plane two-wheel model, and is calculated by substituting each value for the right side of the equation (1).

The variables and constants in each formula are as follows.
<Variable>
γ: vehicle yaw rate V: vehicle speed δ: tire steering angle θh: steering wheel steering angle <constant>
l: vehicle wheel base l _f : distance from vehicle center of gravity to center of front wheel l _r : distance from vehicle center of gravity to center of rear wheel m: vehicle weight k _f : cornering power (front)
k _r : Cornering power (rear)
Gh: Conversion gain from steering wheel steering angle to tire steering angle (steering gear ratio)

  The target yaw rate γ_tgt (γ on the left side of equation (1)) is calculated from equation (1) using the vehicle speed V and the tire steering angle δ as variables. Since the tire steering angle δ in equation (1) cannot be directly sensed, it is calculated from equation (2) by multiplying the steering angle θh by the conversion gain Gh. A steering gear ratio is used as the conversion gain Gh. In addition, the constant A in the equation (1) is a constant representing the characteristics of the vehicle, and is obtained from the equation (3). The target yaw rate γ_tgt calculated by the target yaw rate calculation unit 204 is input to the subtraction unit 212.

  The vehicle yaw rate calculation unit 206 calculates the yaw rate model value γ_clc from the following equation for calculating the vehicle yaw rate. Specifically, the yaw rate model value is obtained by substituting the vehicle speed V and the steering angle θh of the steering wheel into the following expressions (4) and (5) and solving the expressions (4) and (5) simultaneously. γ_clc (γ in the equations (4) and (5)) is calculated. Since equation (1) can be derived from equations (4) and (5), vehicle yaw rate calculation unit 206 is similar to target yaw rate calculation unit 204 based on steering angle θh and vehicle speed V. The yaw rate model value γ_clc may be calculated from the equation (1) of the vehicle model by a technique. The yaw rate model value γ_clc is output to the yaw rate F / B calculation unit 208. In addition, the yaw rate model value γ_clc is input to the subtraction unit 210.

  On the other hand, the actual yaw rate γ (hereinafter referred to as the actual yaw rate γ_sens) of the vehicle 1000 detected by the yaw rate sensor 142 is input to the subtraction unit 210. The subtracting unit 210 subtracts the yaw rate model value γ_clc from the actual yaw rate γ_sens to obtain a difference γ_diff between the actual yaw rate γ_sens and the yaw rate model value γ_clc. The difference γ_diff is input to the weighting gain calculation unit 218.

  The weighting gain calculation unit 218 calculates the weighting gain a based on the difference γ_diff between the actual yaw rate γ_sens and the yaw rate model value γ_clc.

The yaw rate F / B calculation unit 208 receives the yaw rate model value γ_clc, the actual yaw rate γ_sens, and the weighting gain a. The yaw rate F / B calculation unit 208 calculates the feedback yaw rate γ_F / B by weighting the yaw rate model value γ_clc and the actual yaw rate γ_sens by the weighting gain a based on the following equation (6). The calculated feedback yaw rate γ_F / B is output to the subtracting unit 212.
γ_F / B = a × γ_clc + (1−a) × γ_sens (6)

  FIG. 7 is a schematic diagram showing a gain map when the weighting gain calculation unit 218 calculates the weighting gain a. As shown in FIG. 7, the value of the weighting gain a varies between 0 and 1 according to the reliability of the vehicle model. A difference (deviation) γ_diff between the yaw rate model value γ_clc and the actual yaw rate γ_sens is used as an index for improving the reliability of the vehicle model. As shown in FIG. 7, the gain map is set so that the value of the weighting gain a increases as the absolute value of the difference γ_diff decreases. The weighting gain calculation unit 218 performs the map processing of FIG. 7 on the difference γ_diff and calculates the weighting gain a according to the reliability of the vehicle model.

  In FIG. 7, the weighting gain a is a value from 0 to 1 (0 ≦ a <1). When −0.05 [rad / s] ≦ γ_diff ≦ 0.05 [rad / s], the weighting gain a is 1 (a = 1).

  When 0.05 <γ_diff, or when γ_diff <−0.05, the weighting gain a is set to 0 (a = 0).

When 0.05 [rad / s] <γ_diff <0.1 [rad / s], the weighting gain a is calculated by the following equation.
a = −20 × γ_diff + 2

When −0.1 [rad / s] ≦ γ_diff <−0.05 [rad / s], the weighting gain a is calculated by the following equation.
a = + 20 × γ_diff + 2

  A region A1 of the gain map shown in FIG. 7 is a region where the difference γ_diff approaches 0, a region where the S / N ratio of the actual yaw rate γ_sens is small, and a region where the tire characteristics are linear (dry road surface). The reliability of the yaw rate model value γ_clc calculated from the calculation unit 206 is high. Therefore, the feedback yaw rate γ_F / B is calculated with the weighting gain a = 1 and the distribution of the yaw rate model value γ_clc as 100% from the equation (6). Thereby, the influence of the noise of the yaw rate sensor 142 included in the yaw rate γ_sens can be suppressed, and the sensor noise can be excluded from the feedback yaw rate γ_F / B. Therefore, it is possible to suppress the vibration of the vehicle 1000 and improve the riding comfort.

  Here, as a factor that causes a difference between the actual yaw rate γ and the yaw rate model value γ_clc obtained from the vehicle model, the dynamic characteristics of the tire shown in FIG. 8 can be cited. As shown in FIG. 8, in the characteristic indicating the relationship between the slip angle and the lateral acceleration, the sensor of the yaw rate sensor 142 is in a linear region where the lateral acceleration is linear with respect to the slip angle (a region where the steering speed is relatively slow). The effect of noise occurs. The planar two-wheel model described above assumes a region in which the relationship between the tire slip angle and the lateral acceleration (tire cornering characteristics) is linear. In this linear region, the actual yaw rate γ and the yaw rate model value γ_clc are substantially equal. Match.

  On the other hand, in the region where the cornering characteristic of the tire is nonlinear, the yaw rate and lateral acceleration of the actual vehicle become nonlinear with respect to the steering angle and slip angle, and the two-wheeled model and the yaw rate sensed by the actual vehicle deviate. In such a transient non-linear region, noise does not occur due to the sensor characteristics of the yaw rate sensor 142, so the actual yaw rate γ can be used. The nonlinear region corresponds to, for example, the timing of switching the steering, and corresponds to the characteristic of the region A5 surrounded by the broken line in FIG. When the actual yaw rate γ exceeds the yaw rate model value γ_clc, it corresponds to a non-linear region and is not affected by sensor noise. Therefore, by using the actual yaw rate γ, control based on the true value is possible. If a model that takes into account tire nonlinearity is used, control based on the yaw rate becomes complicated, but according to the present embodiment, the reliability of the yaw rate model value γ_clc can be easily determined based on the difference γ_diff. In the non-linear region, the actual yaw rate γ can be increased and used. Further, a region that is hardly affected by the dynamic characteristics of the tire can be dealt with by the yaw rate model value γ_clc.

  In addition, a gain map area A2 shown in FIG. 7 is an area where the difference γ_diff is large, which corresponds to a wet road surface, a snow road, or a turn with a high G, and the limit of tire slipping. It is an area. In this region, the reliability of the yaw rate model value γ_clc calculated from the vehicle yaw rate calculation unit 206 is reduced, and the difference γ_diff is increased. Therefore, the feedback yaw rate γ_F / B is calculated with the weighting gain a = 0 and the distribution of the actual yaw rate γ_sens as 100% from the equation (6). Thus, feedback accuracy is ensured based on the actual yaw rate γ_sens, and feedback control of the yaw rate reflecting the behavior of the actual vehicle is performed. Therefore, the turning of the vehicle 1000 can be optimally controlled based on the actual yaw rate γ_sens. Further, since the tire is in a slipping region, even if the signal of the yaw rate sensor 142 is affected by noise, the driver does not feel it as vibration of the vehicle 1000, and a decrease in riding comfort can be suppressed. As for the setting of the low μ region A2 shown in FIG. 7, the region where the weighting gain κ = 0 may be determined from the design requirements, and the steering stability performance when the vehicle 1000 actually travels on the low μ road surface, You may decide experimentally from comfort etc.

  In addition, a gain map area A3 shown in FIG. 7 is an area (nonlinear area) in which a transition from a linear area to a limit area is performed, and the yaw rate model value γ_clc is considered in consideration of tire characteristics of the actual vehicle 1000 as necessary. And the distribution (weighting gain a) of the actual yaw rate γ_sens are changed linearly. In the transition from the region A1 (high μ region) to the region A2 (low μ region) or in the region transitioning from the region A2 (low μ region) to the region A1 (high μ region), the torque associated with the sudden change in the weighting gain a In order to suppress fluctuations and fluctuations in the yaw rate, the weighting gain a is calculated by linear interpolation.

  A gain map region A4 shown in FIG. 7 corresponds to a case where the actual yaw rate γ_sens is larger than the yaw rate model value γ_clc. For example, when an incorrect parameter is input to the vehicle yaw rate calculation unit 206 and the yaw rate model value γ_clc is erroneously calculated, control can be performed using the actual yaw rate γ_sens based on the map of the region A4. It should be noted that the range of the weighting gain a is not limited to 0 to 1, and the configuration of the present invention can be changed so that an arbitrary value can be taken as long as the range is established as vehicle control. Enter into a possible category.

The subtraction unit 212 subtracts the feedback yaw rate γ_F / B from the control target yaw rate γ_tgt input from the target yaw rate calculation unit 204 to obtain a difference Δγ between the control target yaw rate γ_tgt and the feedback yaw rate γ_F / B. That is, the difference Δγ is calculated from the following equation (7).
Δγ = γ_Tgt−γ_F / B (7)
The difference Δγ is input to the vehicle body additional moment calculation unit 222 as a yaw rate correction amount. Further, the difference Δγ is input to the low μ determination output gain calculation unit 224.

  The vehicle body additional moment calculation unit 222 calculates the vehicle body additional moment Mg based on the input difference Δγ so that the difference Δγ becomes 0, that is, the control target yaw rate γ_tgt matches the feedback yaw rate γ_F / B. To do. Specifically, the vehicle body additional moment Mg is calculated from the following equation (8). As a result, the vehicle body additional moment Mg necessary for turning at the center position of the vehicle 1000 is obtained.

  On the other hand, the theoretical left / right difference rotation calculation unit 220 calculates a left / right difference rotation theoretical value ΔNew_clc based on the vehicle speed V and the steering angle θh. The left-right differential rotation theoretical value ΔNew_clc is the rotational speed difference between the left and right rear wheels 104 and 106 that is geometrically determined according to the radius of rotation. Further, the subtracting unit 214 calculates a left / right difference rotation actual value ΔNew_real which is a difference between the rotation speed of the left rear wheel 104 and the rotation speed of the right rear wheel 106. Note that the left-right difference rotation actual value ΔNew_real can be obtained from the difference in rotation speed between the left and right wheel speed sensors 127, 128. The left-right differential rotation actual value ΔNew_real may be obtained from the left and right front wheels 100 and 102.

The left / right difference rotation theoretical value ΔNew_clc and the left / right difference rotation actual value ΔNew_real are input to the subtracting unit 216. The subtracting unit 216 calculates ΔNew by subtracting the right / left difference rotation actual value ΔNew_real from the left / right difference rotation theoretical value ΔNew_clc. That is, ΔNew is calculated from the following equation. ΔNew is input to the low μ determination output gain calculation unit 224.
ΔNew = ΔNew_clc−ΔNew_real

  The low μ determination output gain calculation unit 224 calculates a low μ output gain μG based on the inputted differences Δγ and ΔNew. FIG. 9 is a flowchart illustrating a process in which the low μ determination output gain calculation unit 224 calculates the low μ output gain μG. First, in step S <b> 10, the differences Δγ and ΔNew are input to the low μ determination output gain calculation unit 224. In the next step S11, it is determined whether or not | ΔNew | ≧ 150 [rpm]. If | ΔNew | ≧ 150 [rpm], the process proceeds to step S12. In step S12, it is determined whether or not | Δγ | ≧ 0.075 [rad / s]. If | Δγ | ≧ 0.075 [rad / s], the process proceeds to step S14. When the process proceeds to step S14, the absolute value of the difference ΔNew between the left-right differential rotation theoretical value ΔNew_clc and the left-right differential rotation actual value ΔNew_real is greater than or equal to a predetermined value (= 150 [rpm]), and the control target yaw rate γ_tgt and the feedback yaw rate Since the absolute value of the difference from γ_F / B is equal to or greater than a predetermined value (= 0.075 [rad / s]), it is determined that the friction coefficient μ of the road surface is low (low μ state), and the low μ output gain μG Is 0.1 (μG = 0.1).

  On the other hand, if | ΔNew | <150 [rpm] in step S11 or if | Δγ | <0.075 [rad / s] in step S12, the process proceeds to step S18. When the process proceeds to step S18, it is determined that the friction coefficient μ with the road surface is high (high μ state), and the low μ output gain μG is set to 1 (μG = 1).

  Further, after step S14, the process proceeds to step S16. In step S16, it is determined whether or not | Δγ | <0.075 [rad / s]. If | Δγ | <0.075 [rad / s], the friction coefficient μ with the road surface is set. It is determined that the state has changed from the low state to the high state, and the process proceeds to step S18 to set the low μ output gain μG to 1 (μG = 1). On the other hand, if | Δγ | ≧ 0.075 [rad / s], the process returns to step S14 and the state of μG = 0.1 is continued.

  The low μ output gain μG calculated by the low μ determination output gain calculation unit 224 is input to the multiplication unit 226. The multiplication unit 226 also receives the vehicle body additional moment Mg calculated by the vehicle body additional moment calculation unit 222. The multiplier 226 multiplies the vehicle body additional moment Mg by the low μ output gain μG to calculate a correction value Mg ′ for the vehicle body additional moment Mg. As a result, when the low μ determination output gain calculation unit 224 determines that the low μ state, the vehicle body additional moment Mg is corrected to a value of 1/10.

  The correction value Mg ′ is input to the motor required torque calculation unit 228. The motor required torque calculation unit 228 calculates ΔTv from the following equation (9) using the correction value Mg ′. Then, the motor required torque calculation unit 228 calculates the additional torque Tvmot from the following equation (10). Note that the correction value Mg ′ is substituted for Mg in the equation (9).

  In Expression (9), TrdR is the tread width of the rear wheels 104 and 106. Further, TireR is a tire radius of the front wheels 100 and 102 and the rear wheels 104 and 106, and Gratio is a gear ratio of the gear boxes 120 and 122 of the rear wheels 104 and 106. The correction value Mg ′ of the vehicle body additional moment Mg at the center position of the vehicle 1000 is converted into the motor torque ΔTv of the rear wheels 104 and 106 by Expression (9). Then, the respective motor torques of the rear wheels 104 and 106 necessary for generating the correction value Mg ′ are obtained from the equation (10).

By the way, the driving force of the front wheels 100 and 102 and the rear wheels 104 and 106 is determined by the motor torque instruction value reqTq that is determined from the driver's required driving force (accelerator pedal opening) when the vehicle 1000 is traveling straight. Here, the motor torque instruction value reqTq is calculated from the following equation (11).
reqTq = reqF * TireR * Gratio (11)
In Expression (11), reqF is a required driving force determined from the opening of the accelerator pedal.

  When the vehicle 1000 travels straight, the driving force of each of the four motors 108, 110, 112, 114 that drives the front wheels 100, 102 and the rear wheels 104, 106 is a motor torque instruction value reqTq based on the driver's required driving force reqF. The value is divided into four equal parts (= reqTq / 4). On the other hand, when the vehicle 1000 turns, an additional torque Tvmot based on the vehicle body additional moment Mg calculated from the equation (10) is added to the motor torque command value reqTq of the rear wheels 104 and 106 by torque vectoring control. In the case of right turn, the motor torque instruction value for the left rear wheel 104 is a value obtained by adding the additional torque Tvmot to the motor torque instruction value reqTq / 4 for straight traveling, and the motor torque instruction value for the right rear wheel 106 is straight traveling. This is a value obtained by subtracting the additional torque Tvmot from the motor torque instruction value reqTq / 4. Similarly, in the case of a left turn, the motor torque instruction value of the right rear wheel 106 is a value obtained by adding the additional torque Tvmot to the motor torque instruction value reqTq / 4 when traveling straight, and the motor torque instruction value of the left rear wheel 104 Is a value obtained by subtracting the additional torque Tvmot from the motor torque instruction value reqTq / 4 during straight travel.

Therefore, the motor torque instruction values of the motors 108, 110, 112, and 114 at the time of turning can be expressed by the following equations (12) to (15). The motor required torque calculation unit 228 calculates motor torque instruction values TqmotFl, TqmotFr, TqmotRl, and TqmotRr for each of the motors 108, 110, 112, and 114 based on the equations (12) to (15).
TqmotFl (motor torque instruction value of the left front wheel) = reqTq / 4 (12)
TqmotFr (motor torque instruction value of the right front wheel) = reqTq / 4 (13)
TqmotRl (Left rear wheel motor torque instruction value)
= ReqTq / 4- (± Tvmot) (14)
TqmotRr (Right rear wheel motor torque instruction value)
= ReqTq / 4 + (± Tvmot) (15)
The sign of the additional torque Tvmot is set according to the turning direction.

  Next, processing performed by the control device 200 according to the present embodiment will be described. FIG. 10 is a flowchart showing the overall processing of this embodiment. First, in step S100, it is determined whether or not an ignition key (ignition SW) is on. If the ignition key is turned on, the process proceeds to step S102. If the ignition key is not turned on, the process waits in step S100.

  In step S102, it is determined whether or not the inhibitor position sensor (IHN) 144 indicates the position of P (parking) or N (neutral). If it is the position of P (parking) or N (neutral), step S104 is performed. Proceed to If it is determined in step S102 that the position is not P (parking) or N (neutral), the process proceeds to step S106 to determine whether the ignition key is turned on. If the ignition key is turned on, the process proceeds to step S104. . If the ignition key is off in step S106, the process proceeds to step S108, the vehicle activation process is terminated, and the process returns to step S100.

  In step S104, the starting process of the vehicle 1000 is performed, and in the next step S110, it is determined whether or not the inhibitor position sensor (IHN) 144 indicates the position of D (drive) or R (reverse). When the inhibitor position sensor (IHN) 144 indicates the position of D (drive) or R (reverse), the process proceeds to step S112, and the travel control process is started. On the other hand, if the inhibitor position sensor (IHN) 144 does not indicate the position of D (drive) or R (reverse) in step S110, the process proceeds to step S113 to determine whether or not the ignition key is turned on. If the key is on, the process returns to step S110. If the ignition key is off in step S113, the process proceeds to step S108, the vehicle activation process is terminated, and the process returns to step S100.

  After step S112, the process proceeds to step S114, and the operation amount (accelerator opening) of the accelerator pedal by the driver is detected from the detection value of the accelerator opening sensor 146. In the next step S115, it is determined whether or not the operation amount of the accelerator pedal is 0.1 or more. If the operation amount is 0.1 or more, the process proceeds to step S116. In step S116, the required driving force reqF is calculated based on the operation amount of the accelerator pedal. The required driving force reqF can be calculated based on, for example, a map that defines the relationship between the accelerator opening and the required driving force reqF. On the other hand, when the operation amount of the accelerator pedal is less than 0.1, the process proceeds to step S118, and regenerative braking control of each motor 108, 110, 112, 114 is performed.

  After step S116, the process proceeds to step S120. In step S120, it is determined whether or not the absolute value of the steering angle θh detected by the steering angle sensor 138 is 1 [deg] or more. If the absolute value of the steering angle θh is 1 [deg] or more, step S120 is performed. Proceed to S122. In step S122, the additional torque Tvmot is calculated by the above-described method, and feedback control to the target moment γ_Tgt is performed based on the additional torque Tvmot. Therefore, in the next step S124, the motor torque instruction values of the motors 108, 110, 112, 114 are calculated from the equations (12) to (15) based on the additional torque Tvmot, and the motors 108, 110, 112 are calculated. , 114 is instructed to output. In the next step S126, the acceleration of the vehicle 1000 is detected by the longitudinal acceleration sensor 132 and the lateral acceleration sensor 134. After step S126, the process returns to step S114.

  Next, main processing of the processing of FIG. 10 will be described in detail. FIG. 11 is a flowchart showing the process of step S122 of FIG. Here, FIG. 11 is a flowchart illustrating a process in which the weighting gain calculation unit 218 calculates the weighting gain a. The process of FIG. 11 functions as a process of removing noise of the yaw rate sensor 142 by calculating the feedback yaw rate γ_F / B by apportioning the actual yaw rate γ_sens and the yaw rate model value γ_clc based on the weighting coefficient a. First, in step S200, an actual yaw rate γ_sens and a yaw rate model value γ_clc are acquired. In the next step S201, a difference γ_diff between the actual yaw rate γ_sens and the yaw rate model value γ_clc is calculated. In the next step S202, the weighting coefficient a is calculated based on the gain map of FIG. In the next step S204, the feedback yaw rate γ_F / B is calculated based on the above-described equation (6). The calculated feedback yaw rate γ_F / B is used to calculate the difference Δγ in step S224 in FIG.

  FIG. 12 is a flowchart illustrating a process in which the vehicle yaw rate calculation unit 206 calculates the yaw rate model value γ_clc. First, in step S210, the steering angle θh and the vehicle speed V are acquired. In the next step S212, the yaw rate model value γ_clc is calculated by simultaneously solving the equations (4) and (5).

  FIG. 13 is a flowchart showing a process for calculating the additional torque Tvmot. First, in step S220, the target yaw rate calculation unit 204 acquires the steering angle θh and the vehicle speed V. In the next step S222, the target yaw rate γ_Tgt is calculated from the equations (1) to (3) based on the steering angle θh and the vehicle speed V. In the next step S224, a difference Δγ between the control target yaw rate γ_Tgt and the feedback yaw rate γ_F / B is calculated based on the equation (7). In the next step S226, the vehicle body additional moment Mg is calculated from the equation (8).

  In the next step S228, a low μ output gain μG is calculated. The low μ output gain μG is calculated by the low μ determination output gain calculation unit 224 according to the process of FIG. In the next step S230, ΔTv is calculated based on the equation (9), and the additional torque Tvmot is calculated based on the equation (10). Based on the calculated additional torque Tvmot, a motor torque instruction value for each wheel is calculated in step S124 of FIG.

  FIGS. 14 to 17 are characteristic diagrams for explaining how the vehicle 1000 is controlled based on the target yaw rate γ_Tgt when the control according to the present embodiment is performed. Here, FIG. 14 shows a case where the actual yaw rate γ_sens detected by the yaw rate sensor 142 is controlled as the feedback yaw rate γ_F / B for comparison with the present embodiment. As shown in FIG. 14, when the actual yaw rate γ_sens is directly applied to the control, the motors 108, 110, 112, 114 and the inverters 123, 124, 125, 126 have high response characteristics, and therefore the noise included in the actual yaw rate γ_sens. Is recognized as an operation value, and the motor torque instruction value diverges. In the example shown in FIG. 14, the steering angle θh is constant at 0, and the left and right motor torque instruction values are generated differently regardless of the straight traveling state (the state where the steering angle is not steered). In the example shown in FIG. 14, vibration due to noise occurs particularly in the torque instruction value of the motor driving the left rear wheel and the torque instruction value of the motor driving the right rear wheel. Therefore, it can be seen that the noise detected by the yaw rate sensor 142 is the control amount (operation amount) of the motor. Note that the motor that drives the left front wheel and the right front wheel does not feed back the additional torque Tvmot by torque vectoring control. Therefore, vibration due to noise occurs in the torque instruction value of the motor that drives the left front wheel and the right front wheel. Not done.

  FIG. 15 is a characteristic diagram showing the actual yaw rate γ_sens, the target yaw rate γ_Tgt, the difference Δγ between the target yaw rate γ_Tgt and the actual yaw rate γ_sens, and the yaw rate model value γ_clc detected by the yaw rate sensor 142 in the example shown in FIG. In this case, since the steering angle θh is constant as shown in FIG. 13, the values of the target yaw rate γ_Tgt and the yaw rate model value γ_clc are constant at 0. On the other hand, in the characteristic of the actual yaw rate γ_sens detected by the yaw rate sensor 142, vibration is generated due to a noise component. For this reason, vibration due to the noise component also occurs in the difference Δγ between the target yaw rate γ_Tgt and the actual yaw rate γ_sens. As shown in FIG. 15, since γ_sens and Δγ are in opposite directions, when the left and right wheel motor torques are feedback-controlled so that Δγ becomes zero, the left and right wheel motor torque instruction values are shown in FIG. Vibration will occur. In this case, it is conceivable to use a first-order lag filter for general noise removal. However, if these filters are used to control a motor / inverter that is a highly responsive control object, it will be described with reference to FIGS. As it was done, evil will occur.

  On the other hand, FIG. 16 shows a case where feedback control to the target yaw rate γ_Tgt is performed using the yaw rate model value γ_clc instead of the actual yaw rate γ_sens detected by the yaw rate sensor 142. FIG. 16 shows the characteristics of the actual yaw rate γ_sens, target yaw rate γ_Tgt, feedback yaw rate γ_F / B, and yaw rate model value γ_clc detected by the yaw rate sensor 142. Since feedback control to the target yaw rate γ_Tgt is performed using the yaw rate model value γ_clc, the feedback yaw rate γ_F / B is equal to the yaw rate model value γ_clc.

  In the example shown in FIG. 16, cornering is performed by operating the steering wheel 130. In this case, the influence of sensor noise can be removed by performing feedback control using the yaw rate model value γ_clc. However, paying attention to the area A11 surrounded by a broken line, the yaw rate model value γ_clc is deviated from the actual yaw rate γ_sens detected by the yaw rate sensor 142, and in the area A, the yaw rate model value γ_clc does not reflect the vehicle behavior. . Therefore, if the control is performed based on the feedback yaw rate γ_F / B, the actual vehicle behavior cannot be grasped, and the vehicle behavior cannot be controlled.

  FIG. 17 shows control according to the present embodiment, and shows a case where the actual yaw rate γ_sens detected by the yaw rate sensor 142 and the yaw rate model value γ_clc are apportioned by the weighting coefficient to obtain the feedback yaw rate γ_F / B. FIG. 17 shows characteristics of the actual yaw rate γ_sens, target yaw rate γ_Tgt, feedback yaw rate γ_F / B, and yaw rate model value γ_clc detected by the yaw rate sensor 142. The feedback yaw rate γ_F / B is a value obtained by dividing the actual yaw rate γ_sens and the yaw rate model value γ_clc by the weighting coefficient a.

  In the example shown in FIG. 17, a case where the steering wheel 130 is operated left and right alternately to perform slalom traveling is shown. In this case, focusing on the area A12 surrounded by the broken line, the yaw rate model value γ_clc starts to deviate from the actual yaw rate γ_sens detected by the yaw rate sensor 142 when the steering is switched. Therefore, it is determined that the reliability of the yaw rate model value γ_clc has decreased based on the weighting coefficient a, the ratio of the actual yaw rate γ_sens in the feedback yaw rate γ_F / B increases, and the feedback yaw rate γ_F / B finally becomes It matches the actual yaw rate γ_sens. As a result, the feedback yaw rate γ_F / B reflects the vehicle behavior, and the vehicle behavior can be reliably controlled by performing the feedback control based on the feedback yaw rate γ_F / B. Therefore, according to the present embodiment, the sensor noise of the yaw rate sensor 142 can be removed, the delay when the sensor value is filtered can be compensated, and the feedback yaw rate F / according to the vehicle behavior can be compensated. B can be acquired. Therefore, the turning performance of the vehicle 1000 can be greatly improved.

  Note that, when the reliability of the yaw rate model value γ_clc decreases, it is conceivable to perform step switching from the yaw rate model value γ_clc to the actual yaw rate γ_sens. However, in order to suppress the feeling change felt by the driver during a turn, FIG. It is preferable to perform lamp switching based on the weighting coefficient a shown in FIG.

  Further, if the actual yaw rate γ_sens is subjected to filtering processing and substituted into equation (6), the motor instruction torque increases due to the delay accompanying filtering, and particularly in the region where the distribution of γ_clc is small (the weighting factor a is small). It is assumed that the motor command torque increases and the tire slips. Therefore, it is desirable to substitute the sensor value (and the actual yaw rate γ_sens) that is not subjected to the filtering process as it is in the equation (6).

  Next, based on FIG. 18 to FIG. 23, it will be described that drivability can be improved even when the road surface condition changes when the control according to the present embodiment is performed. In general, when control is performed to improve drivability when the road surface friction coefficient (road surface μ) is high, tire contact may be saturated when the road surface μ is low, causing the tire to idle and spin. For this reason, in this embodiment, as described above, the left-right differential rotation actual value ΔNew_real is subtracted from the left-right differential rotation theoretical value ΔNew_clc to calculate ΔNew, and if | ΔNew | ≧ 150 [rpm], the low μ state is set. Determine and set the low μ output gain μG to 0.1. As a result, the value of the additional torque Tvmot obtained from the equation (10) becomes a value that is suppressed according to the road surface μ, and the torque vectoring amount of the left and right wheels is suppressed, and the idling due to the idling of the wheels is reliably suppressed. Is possible.

  18 to 20 are characteristic diagrams showing a case where slalom traveling is performed on a low μ road surface (such as a snowy road), and shows a case where control using the low μ output gain μG according to the present embodiment is not performed. Yes. Here, FIG. 18 shows the rotational speeds of the front, rear, left and right motors 108, 110, 112 and 114. FIG. 19 shows the steering angle θh, the actual yaw rate γ_sens, and the target yaw rate γ_Tgt. FIG. 20 shows motor torque instruction values (TqmotFl, TqmotFr, TqmotRl, TqmotRr) and vehicle speed V.

  As shown in FIG. 18, when slalom traveling is performed on a low μ road surface, when attention is paid to a region A3 surrounded by a broken line, the rotational speed of the right rear wheel 106 rapidly increases, while the left rear wheel 104 It can be seen that the number of revolutions is 0 and the ground contact of the rear wheel is saturated (the grip is lowered). Further, as shown in FIG. 19, in a region A13 surrounded by a broken line, the actual yaw rate γ_sens is generated in the direction opposite to the steering angle θh and the target yaw rate γ_Tgt. Therefore, it can be seen that the vehicle is spinning. Further, as shown in FIG. 20, in the area A13 surrounded by a broken line, reverse motor torque is generated in the left rear wheel 104 and the right rear wheel 106, and torque is generated in the direction of promoting spin. You can see that

  On the other hand, FIGS. 21 to 23 show the control according to the present embodiment, and show the case where the slalom traveling is performed in the same manner as FIGS. Similar to FIG. 18, FIG. 21 shows the rotational speeds of the front, rear, left and right motors 108, 110, 112, 114. Similarly to FIG. 19, FIG. 22 shows the steering angle θh, the actual yaw rate γ_sens, and the target yaw rate γ_Tgt. Similarly to FIG. 20, FIG. 23 shows motor torque instruction values (TqmotFl, TqmotFr, TqmotRl, TqmotRr).

  In FIG. 21, it can be seen that there is no difference between the left and right motor speeds compared to FIG. 18, and that the grounding is not saturated. In FIG. 22, compared with FIG. 19, the target yaw rate γ_Tgt and the actual yaw rate γ_sens change in the same direction so as to follow the steering angle θh, and the vehicle behavior is reliably controlled. In addition, in FIG. 23, it can be seen that the rear wheel motor torque instruction values (TqmotRl, TqmotRr) are suppressed as compared with FIG. Therefore, it is possible to reliably control the vehicle behavior.

  As described above, according to the present embodiment, when feedback control is performed on the target yaw rate γ_Tgt, a value obtained by dividing the actual yaw rate γ_sens detected by the yaw rate sensor 142 and the yaw rate model value γ_clc as the feedback yaw rate γ_F / B is obtained. The ratio between the actual yaw rate γ_sens and the yaw rate model value γ_clc is changed according to the reliability of the yaw rate model value γ_clc. As a result, when the reliability of the yaw rate model value γ_clc is high, the influence of sensor noise can be reliably suppressed by using the yaw rate model value γ_clc, and drivability can be improved. Further, when the reliability of the yaw rate model value γ_clc is low, the actual yaw rate γ_sens detected by the yaw rate sensor 142 can be used to perform control according to the vehicle behavior.

  The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to such examples. It is obvious that a person having ordinary knowledge in the technical field to which the present invention pertains can come up with various changes or modifications within the scope of the technical idea described in the claims. Of course, it is understood that these also belong to the technical scope of the present invention.

200 Control Device 204 Target Yaw Rate Calculation Unit 206 Vehicle Yaw Rate Calculation Unit 208 Yaw Rate F / B Calculation Unit 222 Vehicle Body Added Moment Calculation Unit

Claims (10)

A target yaw rate acquisition unit that acquires a target yaw rate of the vehicle based on the steering angle and the vehicle speed;
A yaw rate model value calculation unit for calculating a yaw rate model value from the vehicle model;
A yaw rate sensor that detects the actual yaw rate of the vehicle;
The yaw rate model value and the sensor value are distributed by changing a distribution ratio between the yaw rate model value and the sensor value based on a difference between the yaw rate model value and a sensor value detected by the yaw rate sensor, and the yaw rate A feedback yaw rate calculation unit for calculating a feedback yaw rate from the model value and the sensor value;
A vehicle turning control unit that controls turning of the vehicle based on a difference between the target yaw rate and the feedback yaw rate;
A vehicle control device comprising:   The feedback yaw rate calculation unit calculates the feedback yaw rate by making the distribution of the yaw rate model value larger than the sensor value as the difference between the yaw rate model value and the sensor value is smaller. The vehicle control device according to claim 1.   The feedback yaw rate calculation unit calculates the feedback yaw rate by making the distribution of the sensor value larger than the yaw rate model value as the difference between the yaw rate model value and the sensor value increases. The vehicle control device according to 1 or 2.   The vehicle turning control unit individually controls a motor that drives each of the left and right wheels based on a difference between the target yaw rate and the feedback yaw rate. Vehicle control device. A rotational speed difference acquisition unit for acquiring a rotational speed difference between the left and right wheels;
A gain calculation unit that calculates a gain according to the friction coefficient of the road surface based on the rotational speed difference,
5. The vehicle turning control unit according to claim 4, wherein the vehicle turning control unit individually controls the motor that drives each of the left and right wheels based on a difference between the target yaw rate and the feedback yaw rate and the gain. Vehicle control device.   The rotation speed difference acquisition unit acquires a first rotation speed difference between the left and right wheels obtained from the vehicle model and a second rotation speed difference obtained from the rotation speed difference of the motor that drives each of the left and right wheels. The vehicle control device according to claim 5, wherein a difference in rotation speed between the left and right wheels is calculated based on a difference between the first rotation speed difference and the second rotation speed difference.   The said vehicle turning control part controls the motor which drives each of a left-and-right wheel separately so that the said feedback yaw rate may become the said target yaw rate, The one in any one of Claims 1-6 characterized by the above-mentioned. Vehicle control device. The feedback yaw rate calculation unit is characterized by allocating the sensor value and the yaw rate model value using the weighted gain set in accordance with the difference between the sensor value and the yaw rate model values, according to claim 1 The control apparatus of the vehicle in any one of -7. The vehicle turning control unit includes a vehicle body additional moment calculating unit that calculates a moment to be applied to the vehicle body based on a difference between the target yaw rate and the feedback yaw rate.
A correction unit for correcting the moment based on the gain;
The vehicle control device according to claim 5, further comprising: a motor required torque calculation unit that calculates a torque instruction value of the motor that drives each of the left and right wheels based on the corrected moment. . Obtaining a target yaw rate of the vehicle based on the steering angle and the vehicle speed;
Calculating a yaw rate model value from the vehicle model;
Detecting the actual yaw rate of the vehicle with a yaw rate sensor;
The yaw rate model value and the sensor value are distributed by changing a distribution ratio between the yaw rate model value and the sensor value based on a difference between the yaw rate model value and the sensor value detected by the yaw rate sensor, and the yaw rate Calculating a feedback yaw rate from the model value and the sensor value;
Controlling turning of the vehicle based on a difference between the target yaw rate and the feedback yaw rate;
A vehicle control method comprising:

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