JP7044010B2 - Suspension characteristic adjustment method and suspension characteristic adjustment device - Google Patents

Description

The present invention relates to a suspension characteristic adjusting method and a suspension characteristic adjusting device.

A technique for adjusting suspension characteristics based on the undulation state of the road surface in front is known. For example, the suspension device described in Patent Document 1 is provided between the actuator and the pump, and supplies the liquid discharged from the pump to the actuator to expand and contract the actuator, and the vehicle front detected by the preview sensor. It is equipped with a controller that controls the pump by finding the target rotation speed of the pump based on the road surface displacement of the pump.

International Publication No. 2017/086014 Pamphlet

When adjusting the suspension characteristics by predicting the vertical vibration of the vehicle body in the future based on the undulating state of the road surface in front, the information on the undulating state of the road surface in the predetermined range (hereinafter referred to as "preview range") in front is predicted. use.
In this case, if the preview range is too long, the detection distance of the sensor becomes long, which causes a decrease in detection accuracy and an increase in calculation load. On the other hand, it takes a certain length of preview range to determine the tendency of undulations.
It is an object of the present invention to predict future vertical vibration of the vehicle body based on the undulating state in the range of the optimum length of the road surface ahead and adjust the suspension characteristics.

In the suspension characteristic adjusting method according to one aspect of the present invention, the natural vibration cycle of the suspension of the own vehicle is calculated, the undulating state of the road surface in front of the own vehicle is detected, and the natural vibration cycle is based on the position of the own vehicle. The vertical vibration of the vehicle body in the predicted section is predicted based on the undulation state detected in the range up to the position ahead by the distance corresponding to the length of the predicted section, which is the set time, and the vehicle body is predicted based on the predicted vertical vibration. Adjust the suspension characteristics to suppress vertical vibration.

In the suspension characteristic adjusting method according to another aspect of the present invention, the natural vibration cycle of the suspension of the own vehicle is calculated, the undulating state of the road surface in front of the own vehicle is detected, and the natural vibration cycle is based on the position of the own vehicle. Suspension that predicts the vertical vibration of the vehicle body in the future based on the undulation state detected in the range up to the position ahead by the preview distance, which is the set distance, and suppresses the vertical vibration of the vehicle body based on the predicted vertical vibration. Adjust the characteristics of.

According to the aspect of the present invention, the suspension characteristics can be adjusted by predicting the vertical vibration of the vehicle body in the future based on the undulation state in the range of the optimum length of the road surface in front.

It is a schematic block diagram of an example of the suspension characteristic adjusting apparatus of embodiment of this invention. It is explanatory drawing of the road surface sensor of FIG. It is a schematic block diagram of an example of the active type suspension of FIG. It is a characteristic diagram which shows the relationship between the command current and the control pressure in a pressure control valve. It is a block diagram which shows an example of the functional structure of the controller of FIG. It is explanatory drawing of the preview distance. It is explanatory drawing of the adjustment example of the detection distance of a road surface sensor. It is a graph which shows the relationship between the predicted interval length and the spring acceleration when the spring acceleration is used as an evaluation function. It is a graph which shows the relationship between the predicted interval length and the spring velocity when the spring velocity is used as an evaluation function. It is a schematic diagram of the vibration of a car body. It is explanatory drawing of the difference between the control amount optimized by using the prediction interval of the half cycle of a natural vibration cycle, and the ideal control amount. It is explanatory drawing of the difference between the control amount optimized by using the prediction interval longer than the half cycle of a natural vibration cycle, and the ideal control amount. It is a flowchart of an example of the suspension characteristic adjustment method of embodiment of this invention.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. It should be noted that each drawing is a schematic one and may differ from the actual one. Further, the embodiments of the present invention shown below exemplify devices and methods for embodying the technical idea of the present invention, and the technical idea of the present invention includes the structure, arrangement, etc. of components. Is not specified as the following. The technical idea of the present invention may be modified in various ways within the technical scope specified by the claims described in the claims.

(Constitution)
See FIG. The suspension characteristic adjusting device 1 adjusts the suspension characteristics based on the undulation state of the road surface in front of the vehicle (hereinafter referred to as "own vehicle") on which the suspension characteristic adjusting device 1 is mounted.
The suspension characteristic adjusting device 1 includes a vehicle body sensor 2, a road surface sensor 3, a vehicle speed sensor 4, a controller 5, and an active suspension 6.

The vehicle body sensor 2 detects the 6-axis motion of the vehicle body on the spring of the own vehicle and the 3-axis motion of the vehicle body under the spring in the vertical direction, the horizontal direction, and the front-rear direction as the state of the vehicle body. Hereinafter, the three-axis motion in the vertical direction, the horizontal direction, and the front-back direction is referred to as "bounce".
For example, the vehicle body sensor 2 may detect the acceleration of the bounce on the spring, the pitch angular velocity on the spring, the roll angular velocity, and the yaw angular velocity, and the acceleration of the bounce under the spring.

The vehicle body sensor 2 may detect the displacement instead of the acceleration of the bounce, or may detect the speed.
The vehicle body sensor 2 may detect pitch angular displacement, roll angular displacement, and yaw angular displacement instead of pitch angular velocity, roll angular velocity, and yaw angular velocity, and may detect pitch angular acceleration, roll angular acceleration, and yaw angular acceleration. It may be detected.
The vehicle body sensor 2 outputs a vehicle body condition signal indicating the detected vehicle body condition to the controller 5.

The road surface sensor 3 detects the undulating state of the road surface in front of the traveling own vehicle. See FIG. The road surface sensor 3 is provided, for example, at the front end of the vehicle body of the own vehicle 7, and detects a predetermined detection distance L away from the front wheels of the own vehicle 7 in order to detect the undulating state of the road surface on which the own vehicle 7 is going to travel. The road surface displacement on the road surface in front of the position 8 is detected. As the own vehicle 7 moves forward, the detection position 8 also moves forward, thereby scanning the road surface displacement at the position in front of the own vehicle 7. The road surface sensor 3 sequentially detects the road surface displacement at the detection position 8 in a predetermined sampling cycle, and sequentially outputs an undulating state signal representing the road surface displacement at each detection position 8 to the controller 5.

The road surface sensor 3 may be any sensor that can detect the displacement of the front road surface at the detection position 8 away from the own vehicle 7, for example, a millimeter wave radar, a microwave radar, a laser radar, an optical camera, an ultrasonic sonar, and an infrared sensor. May be. The location where the road surface sensor 3 is installed may be any position as long as it can detect the displacement of the road surface, and may not be the front end of the vehicle body.

See FIG. The vehicle speed sensor 4 detects the wheel speed of the own vehicle and calculates the vehicle speed V of the own vehicle based on the wheel speed. The vehicle speed sensor 4 outputs a vehicle speed signal indicating the calculated vehicle speed V to the controller 5. The vehicle speed sensor 4 may be a pulse generator such as a rotary encoder that measures a wheel speed pulse, for example.

The controller 5 is an active suspension 6 so as to suppress the vehicle body behavior based on the vehicle body condition signal output from the vehicle body sensor 2, the undulation state signal output from the road surface sensor 3, and the vehicle speed signal output from the vehicle speed sensor 4. It is an electronic control unit (ECU) that adjusts the characteristics of.
The controller 5 includes a processor such as a CPU (Central Processing Unit) and an MPU (Micro-Processing Unit), and peripheral parts such as a storage device.

The storage device may include any of a semiconductor storage device, a magnetic storage device, and an optical storage device. The storage device may include a memory such as a register, a cache memory, a ROM (Read Only Memory) and a RAM (Random Access Memory) used as the main storage device.
The processor realizes the function of the controller 5 described below by executing a computer program stored in the storage device.
The controller 5 may be realized by a functional logic circuit set in a general-purpose semiconductor integrated circuit. For example, the controller 5 may have a programmable logic device (PLD: Programmable Logic Device) such as a field-programmable gate array (FPGA).

The controller 5 calculates a control amount for adjusting the operating pressure of the hydraulic cylinder of the active suspension 6 interposed between the vehicle body side member and the wheel side member based on the vehicle body state signal, the undulation state signal, and the vehicle speed signal. Then, the control amount is output to the active suspension 6.
The active suspension 6 adjusts the working pressure of the hydraulic cylinder based on the control amount calculated by the controller 5 to change the characteristics of the active suspension 6.

See FIG. Reference numeral 10 indicates a vehicle body side member, and reference numerals 11FL to 11RR indicate front left to rear right wheels.
The active suspension 6 has hydraulic cylinders 18FL to 18RR as actuators interposed between the vehicle body side member 10 and the wheel side members 14 of the wheels 11FL to 11RR, and the operating pressures of these hydraulic cylinders 18FL to 18RR. It is equipped with pressure control valves 20FL to 20RR that are individually adjusted.

Further, the active type suspension 6 supplies hydraulic oil of a predetermined pressure to these pressure control valves 20FL to 20RR via the supply side pipe 21S, and collects the return oil from the pressure control valves 20FL to 20RR through the return side pipe 21R. The hydraulic pressure source 22 and the accumulators 24F and 24R for accumulating pressure inserted in the hydraulic pressure source 22 and the supply side pipe 21S between the pressure control valves 20FL and 20RR are provided.

Each of the hydraulic cylinders 18FL to 18RR has a cylinder tube 18a, and the cylinder tube 18a is formed with a lower pressure chamber L separated by a piston 18c having a through hole in the axial direction, and the piston 18c is formed. Thrust is generated according to the difference in pressure receiving area between the upper and lower surfaces and the internal pressure. The lower end of the cylinder tube 18a is attached to the wheel side member 14, and the upper end of the piston rod 18b is attached to the vehicle body side member 10.

Further, each of the pressure chambers L is connected to the output ports of the pressure control valves 20FL to 20RR via the hydraulic pipe 38. Further, each of the pressure chambers L of the hydraulic cylinders 18FL to 18RR is connected to the accumulator 34 for absorbing under-spring vibration via the throttle valve 32. Further, a coil spring 36 having a relatively low spring constant and supporting the static load of the vehicle body is arranged between each of the hydraulic cylinders 18FL to 18RR above and below the spring.
Each of the pressure control valves 20FL to 20RR is composed of a 3-port proportional electromagnetic pressure reducing valve having a cylindrical valve housing in which a spool is slidably mounted and a proportional solenoid integrally provided therein.

The controller 5 controls the movement distance of the poppet housed in the valve housing, that is, the position of the spool by adjusting the command current i (control amount) supplied to the exciting coil of the proportional solenoid, and controls the supply port and the output port. Alternatively, the hydraulic oil flowing between the hydraulic source 22 and the hydraulic cylinders 18FL to 18RR is controlled via the output port and the return port. As a result, the thrust generated by the hydraulic cylinders 18FL to 18RR is controlled to suppress the vehicle body behavior.

FIG. 4 shows the relationship between the command current i (: iFL to iRR) applied to the exciting coil and the control pressure P output from the output port of the pressure control valve 20FL (to 20RR). When the minimum current value iMIN in consideration of noise, the control pressure P becomes the minimum control pressure PMIN, and when the current value i is increased from this state, the control pressure P increases linearly in proportion to the current value i and becomes the maximum. When the current value is iMAX, the maximum control pressure PMAX corresponding to the set line pressure of the hydraulic source 22 is obtained. The reference code iN indicates a neutral command current, and the reference code PN indicates a neutral control pressure.

Next, the functional configuration of the controller 5 will be described with reference to FIG. The controller 5 includes a vehicle body state acquisition unit 40, a prediction interval setting unit 41, a road surface displacement acquisition unit 42, and a model prediction control unit 43.
The vehicle body condition acquisition unit 40 receives the vehicle body condition signal output from the vehicle body sensor 2. The vehicle body condition acquisition unit 40 acquires vehicle body condition information indicating the vehicle body condition based on the received vehicle body condition signal.

The vehicle body condition information may include, for example, the displacement of the bounce on the spring, the velocity and the acceleration, and the displacement, the velocity and the acceleration around the pitch axis, the roll axis and the yaw axis. Further, the vehicle body state information may include information on the displacement, velocity and acceleration of the bounce under the spring.
When the vehicle body state signal is displacement information, the vehicle body state acquisition unit 40 can acquire velocity information and acceleration information by differentiating the displacement information.

When the vehicle body state information is the speed information, the vehicle body state acquisition unit 40 can acquire the displacement information by integrating the speed information, and can acquire the acceleration information by differentiating the speed information.
When the vehicle body state information is acceleration information, the vehicle body state acquisition unit 40 can acquire displacement information and velocity information by integrating the acceleration information.
The vehicle body condition acquisition unit 40 outputs vehicle body condition information indicating the vehicle body condition at the current time t0 to the model prediction control unit 43. Further, the vehicle body state acquisition unit 40 outputs the speed information of the bounce on the spring to the prediction interval setting unit 41.

The prediction interval setting unit 41 sets the length Tp (hereinafter referred to as “prediction interval length”) of the prediction interval of the model prediction control by the model prediction control unit 43.
The prediction interval is a future finite time interval that predicts the state of the controlled object in model prediction control.

In the model prediction control, the state of the controlled object at the time t0 + 1, t0 + 2, ..., T0 + Tp + 1 is predicted based on the input to the controlled object at the time t0, t0 + 1, ..., T0 + Tp.
Then, based on the predicted time t0 + 1, t0 + 2, ..., T0 + Tp + 1, an evaluation function indicating the control performance in the prediction interval is calculated, and the control amount that minimizes this evaluation function is searched for using an optimization problem or the like. do.

The prediction interval setting unit 41 may set the prediction interval length Tp based on, for example, the natural frequency of the active suspension 6.
In this case, for example, the prediction interval setting unit 41 receives the speed information of the bounce on the spring output by the vehicle body state acquisition unit 40. The prediction interval setting unit 41 calculates the natural frequency of the active suspension 6 based on the bounce speed on the spring. For example, the prediction interval setting unit 41 may calculate the natural frequency of the active suspension 6 by frequency analysis of the bounce speed on the spring.

For example, the prediction interval setting unit 41 may set the prediction interval length Tp in the natural frequency period of the active suspension 6 or a half period thereof. The reason will be described later.
The prediction interval setting unit 41 outputs the set predicted section length Tp to the road surface displacement acquisition unit 42 and the model prediction control unit 43.

The road surface displacement acquisition unit 42 sequentially receives the undulation state signal output from the road surface sensor 3 at a predetermined cycle. The road surface displacement acquisition unit 42 temporarily accumulates the undulation state signal for a predetermined time, and discards the old undulation state signal in order. For example, the road surface displacement acquisition unit 42 may discard the undulation state signal at the point where the own vehicle has passed.
Further, the road surface displacement acquisition unit 42 receives the vehicle speed signal from the vehicle speed sensor 4. The road surface displacement acquisition unit 42 has a position range in which the vehicle is predicted to travel in a future time section from the current time t0 to the time (t0 + Tp) ahead of the predicted section length Tp based on the vehicle speed V and the predicted section length Tp. To set.

See FIG. 6A. The own vehicle 7 traveling at the vehicle speed V moves from the current position p0 to the position pn ahead by the distance Dp (= V × Tp) from the current time t0 to the time (t0 + Tp) ahead of the predicted section length Tp. ..
The distance Dp is the moving distance of the own vehicle 7 determined in correspondence with the predicted section length Tp and the vehicle speed V, and is hereinafter referred to as "preview distance Dp". The preview distance Dp is determined by the product of the predicted section length Tp and the vehicle speed V of the own vehicle 7.

Then, the road surface displacement acquisition unit 42 receives the time t0, t0 + 1, ..., T0 + Tp between the current time t0 and the time (t0 + Tp) ahead of the predicted section length Tp, respectively, at each point pi ( The undulation state signal of i = 0, 1, ..., N) is acquired from the accumulated undulation state signal.
That is, the road surface displacement acquisition unit 42 acquires the undulation state signal detected in the range from the position p0 of the own vehicle 7 at the current time t0 to the position pn ahead by the preview distance Dp.

For example, the time difference Δti (i = 0, 1, ... n) between the past timing when the road surface sensor 3 detects the undulating state of each position pi (i = 0, 1, ... n) and the current time t0 is. It is determined according to the detection distance L of the road surface sensor 3, the preview distance Dp, and the vehicle speed V.
The road surface displacement acquisition unit 42 extracts the undulation state signals acquired at the timings retroactive to these time differences Δti (i = 0, 1, ... n) from the accumulated undulation state signals for a predetermined time. Therefore, the undulation state signal that detects the undulation state of each point pi can be acquired.

As shown in FIG. 6B, the detection distance L of the road surface sensor 3 may be adjusted according to the vehicle speed, and the road surface sensor 3 may be configured to detect the road surface displacement of the front road surface separated by the preview distance Dp. In this case, the undulation state signal detected by the road surface sensor 3 at the current time t0 becomes the undulation state signal of the position pn of the own vehicle at the time t0 + Tp ahead of the predicted section length Tp.

See FIG. The model prediction control unit 43 executes model prediction control based on the vehicle body condition information acquired by the vehicle body condition acquisition unit 40 and the undulation state signal acquired by the road surface displacement acquisition unit 42, thereby causing the active suspension 6 to perform the model prediction control. The control amount of the pressure control valves 20FL to 20RR for adjusting the working pressure of the hydraulic cylinders 18FL to 18RR is determined. Hereinafter, the controlled amount of the pressure control valves 20FL to 20RR is simply referred to as a “controlled amount”.
The model prediction control unit 43 includes a state predictor 50, an evaluation unit 51, and an optimization unit 52.

The state predictor 50 receives the vehicle body condition information at the current time t0 from the vehicle body condition acquisition unit 40. Further, the state predictor 50 receives the undulating state signals of the positions pi (i = 0, 1, ... n) at which the own vehicle reaches the times t0, t0 + 1, ..., T0 + Tp from the road surface displacement acquisition unit 42. Further, the state predictor 50 receives candidates for each control amount at time t0, t0 + 1, ..., T0 + Tp from the optimization unit 52.

The state predictor 50 is a state quantity of the vehicle body at time t0 + 1, t0 + 2, ..., T0 + Tp + 1 based on the vehicle body state information at the current time t0, the undulation state signal of each of the time t0, t0 + 1, ..., T0 + Tp and the candidate of the control amount. Predict each. For example, the state predictor 50 predicts the displacement, velocity and acceleration of the bounce on the spring, and the displacement, velocity and acceleration around the pitch axis, around the roll axis and around the yaw axis, and the displacement, velocity and acceleration of the bounce under the spring. You can do it.

The state predictor 50 may be, for example, a model predictor that predicts the state of the vehicle body using a differential equation that expresses a model of the vehicle body behavior, and is a deep neural network (DNN: Deep Neural) that has learned the model of the vehicle body behavior. Network) may be used.
The state predictor 50 outputs the state quantity of the vehicle body at the predicted times t0 + 1, t0 + 2, ..., T0 + Tp + 1 to the evaluation unit 51.

The evaluation unit 51 evaluates the control performance of the candidate control amount at each time t0, t0 + 1, ..., T0 + Tp by calculating the cost using a predetermined evaluation function based on the state amount predicted by the state predictor 50. do. Here, for example, the acceleration on the spring or the speed on the spring may be calculated as an evaluation function (cost) in order to suppress the behavior of the vehicle body. The evaluation unit 51 outputs the calculated cost to the optimization unit 52.

The optimization unit 52 optimizes each control amount candidate at time t0, t0 + 1, ..., T0 + Tp so as to minimize the cost calculated by the evaluation unit 51.
The optimization unit 52 may optimize the control quantity candidate based on, for example, an iterative method using the differential value of the evaluation function.
Further, for example, the optimization unit 52 may optimize the control amount candidate based on the heuristic method of directly searching for the optimum solution by trial and error. Heuristics may use, for example, genetic algorithms, particle swarm optimization, artificial bee colony algorithms.
The optimization unit 52 outputs the control amount at time t0 out of the control amounts at time t0, t0 + 1, ..., T0 + Tp optimized by the search to the pressure control valves 20FL to 20RR of the active suspension 6.

(Example of setting predicted section length Tp)
The graph of FIG. 7A shows the relationship between the predicted interval length Tp and the spring acceleration when the control amount is optimized by using the spring acceleration as the evaluation function. The solid line shows the relationship when the natural frequency of the active suspension 6 is 0.72 Hz and the natural vibration period is 1.38 seconds.
It can be seen from the graph that the spring acceleration decreases sharply while increasing the predicted interval length Tp from 0 seconds to 0.66 seconds, which is about half the period of the natural vibration cycle, and gradually increases as it increases from 0.66 seconds. ..

The broken line shows the relationship when the natural frequency of the active suspension 6 is 1.31 Hz and the natural vibration period is 0.76 seconds. Similarly, in this case as well, the spring acceleration decreases sharply while increasing the predicted interval length Tp from 0 seconds to 0.33 seconds, which is about half the period of the natural vibration cycle, and gradually increases as it increases from 0.33 seconds. You can see that it does.

Therefore, when the spring acceleration is used as the evaluation function (that is, when the control amount is adjusted so as to suppress the acceleration of the vertical vibration of the vehicle body), the predicted interval length is half the natural vibration cycle of the active suspension 6. Set Tp.
In the present invention, the meaning of "setting to half cycle" is not only when the predicted interval length Tp is set to exactly half cycle, but also to the range including the tolerance as long as the effect peculiar to the present invention is exhibited. Including the case of
For example, in the case where the natural vibration cycle is 0.76 seconds, the half cycle may be set to 0.38 seconds ± 14%, which is a range including the 0.33 seconds.

The graph of FIG. 7B shows the relationship between the predicted interval length Tp and the spring acceleration when the control amount is optimized by using the spring velocity as the evaluation function. The natural frequency of the active suspension 6 is 1.31 Hz, and the natural vibration period is 0.76 seconds.
When the spring speed is used as the evaluation function, it can be seen that the spring speed decreases sharply while increasing the predicted interval length Tp to 0.68 seconds, which is close to the natural vibration period, and gradually increases as it increases from 0.68 seconds. ..

Therefore, when the spring speed is used as the evaluation function (that is, when the control amount is adjusted so as to suppress the vertical vibration speed of the vehicle body), the predicted section length Tp is set in the natural vibration cycle of the active suspension 6. do.
In the present invention, the meaning of "setting to the natural vibration cycle" is not only when the predicted section length Tp is set exactly to the natural vibration cycle, but also in the range including the tolerance as long as the peculiar effect of the present invention is exhibited. Including the case of setting to.
For example, in the case where the natural vibration cycle is 0.76 seconds, the natural vibration cycle may be set to a range of 0.76 seconds ± 11%, which is a range including the above 0.68 seconds.

Next, with reference to FIG. 8, the reason why the predicted section length Tp requires a length of about half the natural vibration cycle of the active suspension 6 will be examined. The solid line schematically represents the vertical displacement on the spring.
It is considered that the vibration of the mechanical system is a superposition of the irregular vibration due to the disturbance on the regular vibration (indicated by the broken line) due to the natural frequency of the mechanical system.

Here, the vibration due to the natural frequency can predict the overall periodicity by observing the half cycle (hatched area) of the natural vibration cycle. Therefore, by setting the prediction interval length Tp in the model prediction control to a half cycle of the natural vibration cycle and making it possible to predict the vibration due to the natural frequency in the model prediction control, regular vibration due to the natural frequency can be achieved. It is considered that the control amount can be optimized so that it can be removed.

Next, when the predicted section length Tp exceeds the length of about half the natural vibration cycle (when the spring speed exceeds the length of the natural vibration cycle when the evaluation function is used), the behavior on the spring exceeds. Examine the reason for the increase and poor control performance.
First, in model prediction control, the amount of calculation increases dramatically as the prediction interval length increases. Therefore, if the prediction interval length becomes long, the optimization process may be completed before the evaluation function becomes sufficiently small, and it may be difficult to converge the evaluation function, resulting in poor control performance.

Further, the results of examining the difference between the control amount optimized by the model predictive control and the ideal control amount are schematically shown in FIGS. 9A and 9B. The solid line is the control amount optimized by the model predictive control, and the broken line shows the ideal control amount. FIG. 9A shows a comparison result when the predicted section length Tp is a half cycle of the natural vibration cycle, and FIG. 9B shows a comparison result when the predicted section length Tp is longer than the half cycle of the natural vibration cycle.

By integrating the difference between the control amount optimized by the model prediction control and the ideal control amount and calculating the area, the overall control performance over the prediction interval can be evaluated.
Then, when the predicted interval length Tp is long, the difference in the controlled variable at time t0 becomes larger than when the predicted interval length Tp is short, even if the area of the difference (that is, the overall control result) is the same. It turned out.
As described above, since it is the control amount at time t0 that is finally output to the active suspension 6, the control amount actually output deviates from the ideal control amount, and the control result deteriorates. Can be considered.

(motion)
Next, an example of the operation of the suspension characteristic adjusting device 1 according to the present embodiment will be described. See FIG.
In step S1, the state predictor 50 is made to learn a model of the vehicle body behavior of the own vehicle.
When the learning of the state predictor 50 is completed, the prediction interval setting unit 41 calculates the natural frequency of the active suspension 6 in step S2.
In step S3, the prediction interval setting unit 41 sets the prediction interval length Tp based on the natural frequency.

In step S4, the road surface displacement acquisition unit 42 sets the preview distance Dp, which is the mileage traveled by the own vehicle in the future predicted section, based on the predicted section length Tp and the vehicle speed V of the own vehicle.
In step S5, the road surface displacement acquisition unit 42 acquires the undulation state signal detected in the range from the position p0 of the own vehicle 7 at the current time t0 to the position pn ahead by the preview distance Dp corresponding to the predicted section length Tp. That is, the undulating state in the range from the position p0 to the position pn is detected.

In step S6, the model prediction control unit 43 executes model prediction control based on the vehicle body condition information acquired by the vehicle body condition acquisition unit 40 and the undulation state signal acquired by the road surface displacement acquisition unit 42, thereby executing the hydraulic cylinder. The working pressure of 18FL to 18RR is adjusted to adjust the characteristics of the active suspension 6.

After that, in step S7, it is determined whether or not the ignition switch (IGN) of the own vehicle is turned off. The process ends when the ignition switch (IGN) is turned off (S7: Y). When the ignition switch (IGN) is on (S7: N), the process proceeds to step S8.

In step S8, the prediction interval setting unit 41 determines whether or not the vehicle characteristics (for example, spring weight) of the own vehicle have changed. When the vehicle characteristics change (step S8: Y), it is necessary to recalculate the natural frequency, so the process returns to step S2. If the vehicle characteristics do not change (step S8: N), the process returns to step S5.

The learning of the state predictor 50 (step S1) may be repeated during traveling, or may be performed at a predetermined time such as at the time of factory shipment or at the time of maintenance. Further, the state predictor 50 may be learned at a predetermined cycle regardless of the frequency of use of the own vehicle, such as every month, every few months, every one year, every few years.
Further, the calculation of the natural frequency (step S2) and the setting of the predicted section length Tp and the preview length Dp (steps S3 and S4) do not have to be repeated during traveling. For example, it may be executed once for each trip (from the start of the engine (ignition ON) to the arrival at the destination (ignition OFF)). In addition, it may be performed at a predetermined time such as at the time of shipment from the factory or at the time of maintenance. In addition, the natural frequency is calculated and the predicted section length Tp and preview length Dp are set in a predetermined cycle that is not related to the frequency of use of the own vehicle, such as every month, every few months, every year, every few years. May be done.

(Effect of embodiment)
(1) The prediction interval setting unit 41 calculates the natural vibration cycle of the active suspension 6 of the own vehicle, and sets the length of the future prediction interval based on the natural vibration cycle. The road surface sensor 3 detects the undulating state of the road surface in front of the own vehicle. The state predictor 50 predicts the vertical vibration of the vehicle body in the predicted section based on the undulating state detected in the range from the position of the own vehicle to the position ahead by the distance Dp corresponding to the length Tp of the predicted section. The evaluation unit 51 and the optimization unit 52 adjust the characteristics of the active suspension 6 so as to suppress the vertical vibration of the vehicle body based on the predicted vertical vibration.

As a result, the optimum prediction interval length Tp can be set, so that an error in the control amount of the active suspension 6 can be suppressed. Therefore, it is possible to adjust the suspension characteristics to the optimum level and suppress the behavior.

(2) The road surface displacement acquisition unit 42 sets the preview distance Dp according to the traveling speed V of the own vehicle and the length Tp of the predicted section, and sets the undulating state from the position of the own vehicle to the position ahead by the preview distance Dp. Detects the undulating state of the road surface.
As a result, the optimum preview distance Dp can be set, so that an error in the control amount of the active suspension 6 can be suppressed. Therefore, it is possible to adjust the suspension characteristics to the optimum level and suppress the behavior.

(3) The prediction interval setting unit 41 sets the length Tp of the prediction interval to a half cycle of the natural vibration cycle of the active suspension 6. The evaluation unit 51 and the optimization unit 52 adjust the characteristics of the active suspension 6 so as to suppress the acceleration of the vertical vibration of the vehicle body based on the predicted vertical vibration.
This makes it possible to suppress the acceleration of the vertical vibration of the vehicle body.

(4) The prediction interval setting unit 41 sets the length Tp of the prediction interval to the natural vibration cycle of the active suspension 6. The evaluation unit 51 and the optimization unit 52 adjust the characteristics of the active suspension 6 so as to suppress the speed of the vertical vibration of the vehicle body based on the predicted vertical vibration.
This makes it possible to suppress the speed of vertical vibration of the vehicle body.

(5) The prediction interval setting unit 41 calculates the natural vibration cycle of the active suspension 6 of the own vehicle. The road surface displacement acquisition unit 42 sets the preview distance Dp based on the natural vibration cycle. The road surface sensor 3 detects the undulating state of the road surface in front of the own vehicle. The state predictor 50 predicts the vertical vibration of the vehicle body in the future based on the undulating state detected in the range from the position of the own vehicle to the position ahead by the preview distance Dp. The evaluation unit 51 and the optimization unit 52 adjust the characteristics of the active suspension 6 so as to suppress the vertical vibration of the vehicle body based on the predicted vertical vibration.

As a result, the optimum preview distance Dp can be set, so that an error in the control amount of the active suspension 6 can be suppressed. Therefore, it is possible to adjust the suspension characteristics to the optimum level and suppress the behavior.

1 ... Suspension characteristic adjustment device, 2 ... Body sensor, 3 ... Road surface sensor, 4 ... Vehicle speed sensor, 5 ... Controller, 6 ... Active suspension, 7 ... Own vehicle, 8 ... Detection position, 10 ... Body side member, 11FL ... Wheels, 11RR ... Wheels, 14 ... Wheel side members, 18a ... Cylinder tubes, 18b ... Piston rods, 18c ... Pistons, 18FL ... Hydraulic cylinders, 18RR ... Hydraulic cylinders, 20FL ... Pressure control valves, 20RR ... Pressure control valves, 21R ... Side piping, 21S ... Supply side piping, 22 ... Hydraulic source, 24F ... Accumulator, 24R ... Accumulator, 32 ... Valve, 34 ... Accumulator, 36 ... Coil spring, 38 ... Hydraulic piping, 40 ... Body condition acquisition unit, 41 ... Prediction Section setting unit, 42 ... Road surface displacement acquisition unit, 43 ... Model prediction control unit, 50 ... State predictor, 51 ... Evaluation unit, 52 ... Optimization unit

Claims (7)

Calculate the natural vibration cycle of the suspension of your vehicle,
Detecting the undulating state of the road surface in front of the own vehicle,
The vehicle body in the predicted section based on the undulating state detected in the range from the position of the own vehicle to the position ahead by the distance corresponding to the length of the predicted section which is the time set based on the natural vibration cycle. Predict vertical vibration,
The characteristics of the suspension are adjusted so as to suppress the vertical vibration of the vehicle body based on the predicted vertical vibration.
Suspension characteristic adjustment method characterized by this. Set the preview distance according to the traveling speed of the own vehicle and the length of the predicted section.
As the undulating state, the undulating state of the road surface from the position of the own vehicle to the position ahead by the preview distance is detected.
The suspension characteristic adjusting method according to claim 1. The length of the prediction interval is set to the half cycle of the natural vibration cycle,
The characteristics of the suspension are adjusted so as to suppress the acceleration of the vertical vibration of the vehicle body based on the predicted vertical vibration.
The suspension characteristic adjusting method according to claim 1 or 2, wherein the suspension characteristic is adjusted. The length of the prediction interval is set to the natural vibration period, and the prediction interval is set to the natural vibration period.
The characteristics of the suspension are adjusted so as to suppress the speed of the vertical vibration of the vehicle body based on the predicted vertical vibration.
The suspension characteristic adjusting method according to claim 1 or 2, wherein the suspension characteristic is adjusted. Calculate the natural vibration cycle of the suspension of your vehicle,
Detecting the undulating state of the road surface in front of the own vehicle,
Based on the undulating state detected in the range from the position of the own vehicle to the position ahead by the preview distance, which is the time set based on the natural vibration cycle, the vertical vibration of the vehicle body in the future is predicted.
The characteristics of the suspension are adjusted so as to suppress the vertical vibration of the vehicle body based on the predicted vertical vibration.
Suspension characteristic adjustment method characterized by this. A road surface sensor that detects the undulation state of the road surface in front of the own vehicle, and
The natural vibration cycle of the suspension of the own vehicle is calculated, and the road surface in the range from the position of the own vehicle to the position ahead by the distance corresponding to the length of the predicted section which is the time set based on the natural vibration cycle. A controller that predicts the vertical vibration of the vehicle body in the predicted section based on the undulation state and adjusts the characteristics of the suspension so as to suppress the vertical vibration of the vehicle body based on the predicted vertical vibration.
Suspension characteristic adjusting device characterized by being provided with. A road surface sensor that detects the undulation state of the road surface in front of the own vehicle, and
The natural vibration cycle of the suspension of the own vehicle is calculated, and in the future based on the undulation state of the road surface in the range from the position of the own vehicle to the position ahead by the preview distance which is the distance set based on the natural vibration cycle. A controller that predicts the vertical vibration of the vehicle body and adjusts the characteristics of the suspension so as to suppress the vertical vibration of the vehicle body based on the predicted vertical vibration.
Suspension characteristic adjusting device characterized by being provided with.

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