JPS63287634A - Control method for vehicle - Google Patents

Abstract

PURPOSE:To enable a control technique, which simulates an economical and comfortable driving technique, to be realized, by applying a human feeling and/or decision quantitatively during control further even a skilled driver's foreseeing decision. CONSTITUTION:A parameter for grasping a vehicle operation condition in accordance with a control purpose is selected first in a step 20, being sorted into plural sections in accordance with the operation condition. An evaluation index is selected and defined in a step 22. A control rule is created in a step 24, and a foreseen value is defined in a step 26. The above described steps are preliminary processing steps, and a main routine part, first grasping the present operative condition in a step 28 and referring the calculated parameter to the section defined in the step 20 then searching a step 30 for the corresponding section, searches a step 32 for an anticipated value of the operation condition. The main routine part evaluates the control rule in a step 34 determining a control value by an output instruction of the control rule, selected in the preceding step, in a step 36 to be output to a controlled means in a step 38.

Description

[Detailed Description of the Invention] (Industrial Application Field) The present invention relates to a vehicle control method, and more specifically to a method for controlling the driving of a vehicle, particularly an automobile, in which non-physical quantities such as human judgment or sensation are controlled. This invention relates to a vehicle control method that has paved the way for its adoption as an element.

(Prior art) In recent years, in automobiles, things that were previously operated manually by the driver are gradually being automated. This can be cited as an example.

(Problem to be Solved by the Invention) In such automatic control technology, methods such as proportional control, proportional-integral control, and proportional-integral-derivative control have conventionally been used, but all of these control methods require physical quantities as input values. It was assumed that only That is, in these methods, parameters indicating the operating state are grasped and input as physical quantities, and control values are calculated and controlled from an appropriate control law. Therefore, it is impossible to include elements such as human senses or judgments that are difficult to clearly grasp with physical quantities into the control elements, and therefore automatic control of the safe, economical, and comfortable manual operation seen by experienced drivers. It was impossible to incorporate it into the method. Furthermore, in the future, skilled drivers will not only be able to recognize the surrounding situations that actually occur while driving and make the necessary judgments to operate the equipment, but also be able to avoid accidents if they act in this way. However, it was undesirable to incorporate such foresight into control.

Furthermore, in the case of conventional control methods, for the same reason, it is not possible to reflect the differences in the senses of individual drivers, or their diversity, during control, and therefore the interaction between each driver and the vehicle cannot be reflected. I was disappointed that I wasn't always able to fully experience the experience. In addition, in the case of conventional control methods, as a result of the refinement and subdivision of control laws,
When a control device implementing this control method is constructed from a microcomputer, there is an inconvenience that a considerable amount of memory is required.

Therefore, an object of the present invention is to provide a vehicle control method that eliminates such drawbacks of the prior art, and which incorporates not only physical quantities but also elements that are difficult to relate to physical quantities such as human senses and judgments during control. In addition to making it possible to
It is an object of the present invention to provide a vehicle control method that makes it possible to incorporate the foresight of an experienced driver into control and pave the way to providing control technology with improved accuracy.

Furthermore, it is possible to further improve the sense of unity when entering the vehicle by opening the way to making it possible to reflect the differences or diversity of the senses of individual drivers in the control without changing the control law. A vehicle control method that requires only a small amount of memory even when this control method is implemented using a control device consisting of a microcomputer, by making it possible to express fine-grained control using simple control laws. The purpose is to provide

(Means for Solving the Problems) In order to achieve the above object, the vehicle control method according to the present invention detects or controls at least one parameter indicating the driving state of the vehicle, as shown in FIG. 1 by a predetermined calculation process, the parameter is divided into a plurality of sections according to a predetermined first rule (step 10), and then at least one first value corresponding to the section is obtained (step 1).
2), then determining (step 14) at least one second value derived according to at least one predetermined second rule based on the first value; A predetermined calculation process is performed to obtain at least one third value (step 16), and a control value is determined based on the third value (step 18).

(Structure and operation of the invention) First, to explain the premise of the present invention, when grasping a state, it is generally done to specify it using physical quantities, but on the other hand, as shown in Figure 2, it is possible to grasp it using set theory. It is also possible to do so. In other words, all states are roughly divided into conditions such as "small", "medium", and "large", and the case where the condition is completely met is considered to be "1", and the case where it is not matched at all is considered to be "0". For example, the specific state a゛ shown in the same figure is 0°5, which can be called medium, but it is small. It can also be understood that the degree to which this can be said is only 0.1. This is a so-called fuzzy set theory way of thinking, but by adopting such fuzzy set theory,
Not only physical quantities are used as factors that indicate driving conditions, but also non-physical quantities such as images and sensations such as ``driveability'' and ``good steering wheel sharpness'' are statistically derived and quantified through psychological analysis. It is possible to incorporate it inside. The present invention relates to a vehicle control method that utilizes such an ambiguous control method using fuzzy set theory.

Here, the structure of the present invention described in the above-mentioned "Means for Solving the Problems" will be further applied. Then, 3rd F(a)(b)
The flowchart shown in (a) shows the work procedure of the preprocessing section before determining the individual control values, and (b) shows the procedure for determining the individual control values based on that. To explain with reference to the flow chart of the preprocessing section showing the work procedure of the main routine section that determines the operation, first, in step 20, parameters for understanding the vehicle operating state are selected according to the control purpose, and the parameters are changed to the operating state. Physical quantities are usually used as the operating condition parameters, but non-physical quantities such as sensations or judgments may also be quantified using appropriate methods.If physical quantities are used, , actual measured values, and calculated values such as their n-th derivatives.Next, in step 22, an evaluation index is selected and defined.The evaluation index is determined based on the above-mentioned parameters, and is controlled as described below. It serves as an index for evaluating the rules.

Next, in step 24, a control law is created.The characteristic feature of the present invention is that the control law is expressed in language, and the output command specified in the control law is expressed in language. The point is that it is a predictive measure that asks about the degree of satisfaction with the evaluation index.

Next, in step 26, a predicted value is defined. This expresses the change in the operating state as a quantitative variation of the parameter, assuming that the above-mentioned output command is executed, and such predicted value data is defined in advance through experiments. It is assumed that the above-mentioned operations have been completed in the preprocessing stage.Next, the main routine section shown in FIG. This is done by determining the parameters.

Subsequently, in step 30, the category defined in step 20 is referred to for the calculated parameter, and a corresponding category is searched.

Subsequently, in step 32, a predicted value of the operating state is retrieved assuming that the specified output command is executed during the aforementioned control period. This is done by searching for the predicted value created in step 26 above.

Subsequently, in step 34, the control law is evaluated by determining to what extent the aforementioned predicted value achieves the degree of satisfaction required by the evaluation index. In this case, if a plurality of evaluation indicators are involved in one control law, the minimum value of the evaluation values is used for evaluation.

If there are multiple control laws, select one of them,
In this case, for example, the control law with the highest evaluation value is selected as the one with the highest degree of satisfaction.

Next, in step 36, a control value is determined based on the output command of the control law selected in the previous step, and in step 38
output to the controlled means. In the above configuration, the work in step 20.28 corresponds to the calculation and classification of parameters (step 10) described above, and the work in step 2
The work in 0.30 was due to the calculation of the first value described above (step 12), and steps 22.24 and 26.3
The work in step 2 is the calculation of the second value described above (step 1
4), the work in step 34 corresponds to the calculation of the third value (step 16), and step 36
．． The work in step 38 corresponds to the determination of the control value described above (step 18).

(Embodiment) Hereinafter, an embodiment of the vehicle control method according to the present invention will be described by taking constant speed driving control '4B (auto cruise) as an example.

For convenience, an apparatus for implementing the present invention will be described first.

FIG. 4 shows the overall configuration of the constant speed traveling device, and will be explained with reference to the same figure. Reference numeral 40 indicates an engine, and the throttle valve 4 of the intake passage 44 extending from the air cleaner 42
Fuel is supplied from a fuel injection device 48 located downstream of 6. The throttle valve 46 is electrically connected via an accelerator sensor 52 to an accelerator pedal 50 provided on the floor of the driver's seat of the vehicle, and is also mechanically connected to a pulse motor 54 to generate its driving force. It is configured to open and close by receiving it. A crank angle sensor (not shown) is disposed near the rotating part of the engine, and an absolute pressure sensor (not shown) is disposed at an appropriate position in the intake passage 44 to detect the absolute pressure in the intake passage.
(also not shown) is arranged to detect the engine speed signal and the absolute pressure signal and send them to the control unit 56. The control unit 56 mainly has an input/output interface and a CPU.
It is composed of a microcomputer consisting of ROM, RAM, etc.

Further, a power transmission device such as a transmission is connected to the next stage of the engine 40, and a vehicle speed signal is detected from the power transmission device via a vehicle speed sensor (not shown) provided at an appropriate position. It is sent to control unit 56. Further, at appropriate positions on the steering wheel (not shown), there are a main switch for turning on/off constant speed driving control, a set switch for driving set and deceleration, and a resume switch for resuming constant speed driving or accelerating. The on/off signal thereof is also input to the control unit 56. Further, a throttle sensor 60 is provided near the throttle valve 46 to detect the valve opening and control the control unit 5.
Send on 6. Further, the operation of a brake pedal 62 disposed in parallel with the accelerator pedal 50 is also input to the control unit 56 via a brake switch 64. The control unit 56 calculates control values based on these input signals and outputs them to the pulse motor 54 via the pulse motor control circuit 66 to control the opening and closing of the throttle valve 46 and also to the fuel injection device 48. output and control its fuel injection.

Next, an embodiment of the vehicle control method according to the present invention will be described by taking constant speed running control as an example with reference to FIG. 5 and subsequent figures. FIGS. 5(a) and 5(b) are flow charts showing the control method. Starting from the preprocessing section flow chart in FIG. 5(a), as described in the flow chart in FIG. 3 above,
First, in step 70, parameters indicating the operating state are selected. In this embodiment, as a parameter, the deviation between the set vehicle speed V SET and the actual vehicle speed IF (km
/h...mph), vehicle speed Vt - first-order differentiated vehicle acceleration α (b/h/s, , , speed change per second), and vehicle speed ■ second-order differentiated acceleration change Δα ( k
m/h to 8/3...The amount of change in acceleration per second (jerk) is used.

Subsequently, in step 72, the parameters are divided into a plurality of categories depending on the operating state. FIG. 6(a) shows this division, and as shown, the parameters VDIF,
α, Δα are 15 from +7 to -7 centering on 0.
(hereinafter referred to as "domain U") (in addition,
In the domain U, the columns are continuous,
Values between them can also be found by interpolation calculation) 0
As shown in the figure (deviation VDIF is -7h/h (hereinafter included) ~
Over the range of +7b/h (inclusive), acceleration α is -1, 4km*/h/s (inclusive) to +1.4
km/h/s (inclusive), and the acceleration change Δα is -2°8 kn/h/s/s (inclusive) to +2.8 km/h/s/s (inclusive) include)
The deviation V is allocated on the domain U over the range of
A negative value of DIF indicates that the actual vehicle speed is lower than the set vehicle speed, and a negative value of acceleration α and its variation Δα indicates a deceleration state. or,
The vertical columns in Figure (a) are the fuzzy labels FL in fuzzy set theory, namely NB, NM, NS, ZO, PS, P.
It is divided into 7 columns by M and PB, and the 105 columns that intersect with the domain column define numerical values from 0'' to ``1'' (hereinafter referred to as ``membership value μ''). . The table (hereinafter referred to as the "membership map") shown in FIG. 5A is stored in the ROM of the microcomputer of the control unit 56.

In addition, each of the above ambiguous labels is N5=NEGATIV
E BIG large in negative direction, N5=NEGAT
IVE MEDIUM Medium in the negative direction, N5=N
EGATIVE SMALL Small in the negative direction,
ZO=ZERO zero, PS=PO3ITIVE SMA
Small in LL positive direction, PM=PO3ITIVE
MEDIUM Medium in positive direction, PB=PO3ITIV
E BIG means large in the positive direction. FIG. 6(b) shows a graph of this.

Subsequently, in step 74, the evaluation index E is selected and similarly classified to create a membership map and stored in the ROM. FIG. 7(a) shows the membership map of the evaluation index, and in this example, the evaluation index is followability EVA, refreshment E FR, comfort ECF, fuel efficiency EF.
As shown in the figure, five of E and safety ESF are selected.
Similar to the membership map in Figure 6(a), the membership values and blobs in Figure 6(a) are divided into a domain U consisting of 15 divisions, and the columns that intersect with each index are filled with values. 1. Membership value μVA, μFR, less than or equal to 0 value
μCF, μFE, μSF are defined. This evaluation index E indicates the superiority or inferiority of the fluctuation state based on the above-mentioned parameters. In other words, followability EVA is the deviation V DIF, refreshing EFR and comfort ECF are the acceleration change amount Δα, fuel efficiency EFE is the acceleration α, and safety ESF is the acceleration change amount Δα.
is based on the deviation V DIF, and indicates the superiority or inferiority of quantitative fluctuations with a function value of 1.0 or less.

Figure (b) is a graph of this. To briefly explain, when the deviation VDIP is zero, there is no difference between the target vehicle speed and the actual vehicle speed, so the membership value μVA has a maximum value of 1. around the domain U-0.
It is defined as 0. It has been empirically recognized that exhilaration EFR gives the occupants a feeling of exhilaration when the amount of change in acceleration continues in the positive direction by a minute amount, so the membership value μ
FR is a curve that slopes upward to the right with respect to the domain U. Comfort ECF is also empirically confirmed to be comfortable when constant acceleration continues, so membership value μCF
is maximum near u=0, where there is no acceleration variation. or,
The fuel efficiency EFE increases as the acceleration or deceleration progresses in the negative direction, so the curve slopes upward to the left, and the safety ESF
Since it has been empirically confirmed that the smaller the deviation, the less the vehicle speed changes and therefore the safer, it similarly becomes maximum near U=O. Although such membership value μE is defined experimentally or empirically, it goes without saying that it is not limited to this and can be set arbitrarily. Note that the membership value of the comfort ECF may be defined based on the elapsed time until the inflection point at which the acceleration changes in the negative direction as a parameter.

Next, in step 76, a control law Ri is created and R
Store in OM. FIG. 8 shows this control law Ri, in which five control laws Ril to R45 are set. In the present invention, the control law is expressed in language, and a predictive agent is included in it. For example, the control law Ril specifies, ``If the throttle is loosened a little, if the tracking performance and comfort are satisfied, loosen the throttle a little.'' The content is also similar. This control law defines an output command Ci, and in this embodiment, the output command Ci is an ambiguous label FLC.
It is indicated by i. In addition, each control law includes one or more evaluation indicators, but which evaluation indicators to include can be arbitrarily determined by determining the causal relationship with the control content. If it is not possible to consider the evaluation index that occurs in the operating state, it may not be included in the control law. In other words, in such a case, evaluation of other important evaluation indicators may be hindered and the control law itself may not be adopted.

Next, in step 78, a predicted value is created.

This is done by applying the control law described above one by one to generate the output command C.
The fluctuation of the operating state when it is assumed that i is executed is expressed as the quantitative fluctuation values of the parameters VDIP, α, Δα (
This is defined as a predicted value P (hereinafter referred to as a predicted value P (VDIFp, αp, Δαp)) and is indicated by an ambiguous label FLp. Figure 9 (a), (b), and (c) are tables of predicted values defined for each parameter (hereinafter referred to as “forecast table”).
). Such a preview table is created in advance through experiments and stored in the aforementioned ROM. FIG. 4(d) shows a graph of these predicted value ambiguous labels FLp.

Next, moving on to the explanation of the main routine part of FIG. 5(b), first, in step 80, it is determined whether or not the aforementioned main switch is on, and if it is not on, is the constant speed driving mode? Ill (AC) is not performed (step i
2).

If the main switch is on, then in step 84, the throttle valve opening θTH is read from the output value of the throttle sensor 60, and the vehicle speed V, acceleration α, and acceleration change amount Δα are calculated from the output value of the vehicle speed sensor. do. In this case, the vehicle speed V is calculated from the average value within a predetermined time, the acceleration α is calculated by dividing the vehicle speed value by seconds, and the acceleration change amount Δα is calculated by further dividing the quotient by seconds.

Next, in step 86, it is determined whether the vehicle speed V calculated in the previous step exceeds a predetermined vehicle speed Vref, for example, 20 h/h, and if it does, then in step 88
At this point, it is determined whether the brake switch 64 is on. In these steps, the predetermined vehicle speed Vref
When the vehicle is moving up the road and the brake switch 64 is on, constant speed running control is not performed (step 82).

Next, in step 90, it is determined whether or not the constant speed driving control is being performed. If the constant speed driving control is not being performed, it is determined in step 92 whether or not the set flag is on. If it is on, the process continues in step 94. The vehicle speed V at that point in time is
is read from the sensor output and set as the set vehicle speed V SET,
In the next step 96, a deviation VDIF is calculated from the set vehicle speed V SET and the vehicle speed ■ detected in the previous step 84. Next, in step 98, the throttle valve opening degree θTH is set as desired. This means that if the driver releases the accelerator pedal immediately after pressing the set switch, the throttle valve closes depending on the driving location. Since the speed may be fast, the valve opening degree θ detected in the previous step 84
If TH does not reach a predetermined valve opening degree corresponding to the set vehicle speed VSET, the valve is opened to that opening degree, and is an initialization operation that is a pre-stage of constant speed driving control. Thereafter, in step 100, the routine shifts to constant speed running control, which will be described later with reference to a flow chart showing a subroutine of constant speed running control in FIG.

If it is determined in step 90 that constant speed driving control is being performed, it is determined in step 102 whether or not the set switch is on, and if it is on, deceleration driving control is performed (step 104).

If the set switch is not turned on in step 102, it is determined in step 106 whether or not the resume switch is turned on, and if it is turned on, acceleration driving is controlled (step 10B), and step 10
If the resume switch is not turned on at step 6, the mode shifts to constant speed driving control. If it is determined in step 92 that the set flag is not on, constant speed driving control is not performed (step 82). In any case, since the gist of the present invention is mainly the constant speed running control in step 100, the explanation of this flow chart will end here.

FIG. 10 is a flow chart showing the AC subroutine of constant speed running control. To explain with reference to the same figure,
First, in step 200, the parameter indicating the current operating state calculated in step 84.96, that is, the deviation VDI
F, the acceleration α and the acceleration change amount Δα are searched for on the domain U with reference to FIG. 6, and then step 2
02,204.206, the corresponding fuzzy labels for each parameter FLVDIF, FLα, FLΔα
Search for. To explain with an example, the current driving state is deviation VDIP = Okm/h, acceleration α = Ofa
n/h/s, acceleration change Δα= Okm/h/s/s
In this case, the value of the domain U is U=O for each parameter. Searching for the ambiguous label of u = OIrH, we get
O, O, 0, 1° o, o, o, o, and their membership value is Z O = 1.0 and the others are 0, so only ZO is relevant as an ambiguous label. Therefore, the search results will be as follows.

Parameter Ambiguous label deviation VDIF ZO Acceleration α ZO Acceleration change amount Δα ZO Next, in step 20, the foreknowledge table in Figure 9 is referred to, and the above ambiguous label F searched in the previous step is
From LVDIF, FLα, FLΔα and the vague label FLCi of the output command Ci of the control laws Ril to R45, the vague label FLp indicating the predicted value P (VDIFP, αp, Δαp) of the parameter in the next (n+1) operating state is calculated. demand. Note that the "next (after n+1)" here means a time later than the current point in time, and assuming that the flow chart in FIG. 5 is started at a predetermined time or every predetermined crank angle, For example, it means the time when the next flow chart is started.In addition, it goes without saying that in this case, it may be the time when the next start or the time after that.

The predicted value is shown in the above-mentioned example as follows.

Control law Output command VDIFp αp ΔαρI
NS NS --NS2 ZOZ
O---- 3PS PS PS PS4 NB
NB --NB5 PB PB
--PB Subsequently, in step 210, the membership value μE (μVA, μFR, μ
CF, μFE, μSF) and the membership value μp of the predicted value ambiguous label FLp, the evaluation value μE for each control law is determined. In the above example, the evaluation index of control law 1 is followability EVA (parameter is VDIF) and comfort ECF (parameter is Δα), and since the output command ambiguous label FLCi of control law 1 is NS, followability is The evaluation value μE of the followability EVA is as shown in Fig. 11(a) (the graph of the followability EVA and the ambiguous label N of the deviation VDIF)
It is obtained by overlapping S and taking the maximum value of the overlapping part, 0°8. Similarly, the ambiguous label for acceleration α is also NS
Therefore, the evaluation value μE of the comfort ECF is 0.7.

Moreover, the evaluation index of control law 2 is only followability EVA (parameter is VDIF), and the ambiguous label of VDIF is ZO, so the evaluation value μE is <1.0 as shown in FIG. 11(c). .

The evaluation index of control law 3 is followability EV^, comfort ECF, fuel efficiency EFE, and safety ESF, so the evaluation value μE
are as shown in Figures 11(d) to (g) (,0,82
, 0,75, 0,15 and 1.0. Similarly, in the case of control law 4, the evaluation value of followability EVA is 0.25, and the comfort EC
The evaluation value of F is 0.2, and the evaluation value of safety ESF is 0.35.
Therefore, in the case of control law 5, the evaluation value of followability EVA is 0.2
5. Refreshing EFI? The evaluation value of is 1.0, and the evaluation value of safety ESF is 0.4. The above is summarized as shown in FIG. 12. Such arithmetic operations are performed by converting a table as shown in the figure into the R of the microcomputer of the control unit 56.
This will be done by securing a calculation space within the AM.

In addition, each time this calculation is completed, an appropriate step (not shown) is performed.
However, if it is reset to zero, it is impossible to distinguish between a true O and an unused 0 when calculating the minimum value, so the reset is set to FF (overflow), and the overflowing value is subject to the minimum value. Exclude from

Subsequently, the final evaluation value μRi of the control law is determined. In this case, since the evaluation value (membership value μE) represents the degree of satisfaction with the evaluation index, the minimum value of each evaluation index is assumed to be "at least within the range that all evaluation indexes are satisfied." Find by taking the value. As a result, the final evaluation value μRi for each control law is as follows.

Control law Minimum evaluation value 10.7 21.0 3 0, 1 5 40.2 5 0.25 Next, in step 212, one of the five control laws is selected. In this case, the larger the final evaluation value μRi of the control law obtained in the previous step, the higher the satisfaction. 2 universal control law Rout
Select as.

This control law 2 says, "If the followability is satisfied when the throttle is not changed, do not change the throttle." Therefore, the output command U (Rout) of this selected control law is The control value is set as Uout. In this case, since the output command U (Rout) is represented by an ambiguous label ZO, it is necessary to convert this ZO into a real value. FIG. 13(a) shows this conversion table, and in the upper column, the aforementioned control value Uout is divided into 15 domain columns u.
In the lower column, the throttle opening θTH (degree), which is the object to be controlled, is correspondingly defined. Figure (b) shows a graph of this. In the case of the actual example, the evaluation value μRi indicating the selected satisfaction level is 1.0, and Uout which gives 1.0 in the ZO ambiguous set is U-0, so the throttle opening θT)l is 0 degrees. Become. Note that if a plurality of values of the output θTH are determined during conversion, the smaller one is selected for safety.

Next, another example will be explained. The current operating status
Deviation VDIP = 3) cm/h, acceleration α = 0°6
h/h/a, acceleration change Δcr -1,2km/h/
Assuming s/s, the search results for each ambiguous label are as follows.

Parameter Ambiguous label deviation VDIF PS, PM acceleration α
PS, PM Acceleration change amount Δα PS, PM Also, the predicted value for each control law is as follows. In this case, since the current driving state is expressed by a plurality of ambiguous labels, there are also a plurality of ambiguous labels.

Control law output V DIF α Δα1
NS ZO, PS ---ZO, PS2
zOPS, P? I ----1-3PS
PM, PB PM, P? l PM, FR4N
B NM, NS---NM, NS5
PB PB, PB ---PB, The predicted value for each PB control law is as follows.

Control law E VA E FRE CFl
1.0, 0.8 --- 1.0, 0.72
0.8, 0.4 --- ---3 0
．． 4,0.25 --- 0.3,0.24 0
．． 4,0.25 --- 0.3,0.25 0
．． 25.0.25 1.0, 1.0 --- Control law E PE E SFl ---
----- 30,15,0,150,65,0,44---0,6
5, 0, 4 5---0, 4, 0, 4 The satisfaction level for each control law is expressed by taking the minimum value as in Example 1, but in Example 2, each evaluation index has multiple evaluations. Since there are values, first choose the larger one of each evaluation index (in the sense that the prediction is more consistent), and then choose the minimum value.

As a result, the minimum value is as follows.

Control law Minimum value 11.0 20.8 3 0.15 40.3 5 0.25 Therefore, the control law l is selected. "Please loosen it a little", and the conversion to the output value is NS.
Since Uout=-2, where is 1.0, θTH=-0,
This means that the valve will open 0.5 degrees.

Returning again to the flow chart of FIG. 5, step 110
The control value is outputted to the pulse motor control circuit 66 to drive the pulse motor 64 and control the throttle valve 46.
open and close to a predetermined degree. At the same time, if necessary, the engine speed signal and absolute pressure signal are also taken into account and a control value is output to the fuel injection device 48 to control fuel injection.

As described above, in this embodiment, by using fuzzy set theory, we have paved the way to incorporating human senses during control, and we have also defined the foresight judgment of a skilled driver in a foresight table and used it during control. As a result, it is possible to achieve even more fine-grained control with a simple control law with high accuracy, improving the driver's attention when entering the vehicle, and improving the safety and economy of experienced drivers. This will pave the way to realizing control that simulates a comfortable driving method during automatic control.

FIG. 14 shows a second embodiment of the present invention, which is similarly applied to constant speed cruise control, and specifically shows another example of the AC subroutine. Explaining according to the flowchart in the figure, after grasping the current operating state at an ambiguous level (steps 300 to 306) as in the first embodiment, similarly in step 308, the forecast value FLp is searched using the forecast table. . The difference from the first embodiment is that the 15th embodiment
As shown in the figure, the output command of the control law is not an ambiguous label (it is expressed as a real value). Therefore, in order to search for the predicted ambiguous label FLp, the real value is
Use the conversion table shown in the figure to convert the label to an ambiguous label and then search. Thereafter, as in the first embodiment, the control law is evaluated in step 310, and in step 312, the output command Rout of the control law that shows the maximum value is set as the control value Uout. Since the output command is given as a real value, re-conversion work as seen in the first embodiment is unnecessary. The remaining configuration is the same as that of the first embodiment, and has the same effects as the first embodiment.

FIG. 17 shows a third embodiment of the present invention, and similarly A
This embodiment shows a modified example of the C subroutine.The present embodiment has a simplified configuration compared to the first and second embodiments, and uses a control law consisting of real values like the second embodiment. This method uses a function as shown in FIG. 18 without using a parameter membership map or a prediction table. In FIGS. 18(a), (b), and (c), the output command (j (i.e., throttle valve opening θTH) is scaled with a real value on the X-axis, and the parameter indicating the operating state is on the y-axis. Scaled with real numbers.

The following will be explained according to the flow chart in Figure 17.
In step 400, the parameters VDIP, α, and Δα indicating the current operating state are detected, and from the output command Ci of the control law in FIG.
Find αp and Δαp. To explain with reference to FIG. 19, if the current deviation is 3 km/h, then the straight line VDIFp is obtained by translating the straight line VDIFp by 31ai/h in ten directions.
” is calculated.The output command Ci of control law 1 is θTl1=
Since it is -1 degree, on the y-axis, if the perpendicular line is extended from -1, the intersecting value VDIP on the y-axis becomes 5, and therefore, the predicted value VDIFp=5 h/h can be obtained.

Subsequently, in step 402, an evaluation value for each control law is determined. This is done by determining the evaluation value μE, in this case 0.2, by crossing a perpendicular line from the 5 km/h position determined in the previous step on the followability EVA graph as shown in FIG. This operation is performed for all control laws, the minimum value is determined in the same way as in the first and second embodiments, and then step 4
04, the control law showing the maximum value is determined, and the output command U (Rout) of the control law is set as the control amount Uout.

In this case, since the output command is expressed as a real value, there is no need to reconvert it, which is the same as in the second embodiment.
Tables may be used in place of the functions shown in the figures.This embodiment has the advantage of a simpler configuration than the first and second embodiments.

(Effects of the Invention) Since the present invention is configured as described above, it not only opens the way to quantifying human sensations and judgments that are difficult to grasp with physical quantities and incorporating them into control, but also enables the foresight of skilled drivers to make predictive judgments. It is possible to realize a control method that simulates a safe, economical, and comfortable driving method by incorporating the following, and has the advantage that finer WI control can be realized with high accuracy using a simple control law. Furthermore, it opens the door to incorporating individual differences in sensation and judgment into control (thereby making it possible to realize control that further improves the sense of unity when entering a vehicle, and
Even when this control method is implemented using a control device consisting of a microcomputer, it has the advantage that a relatively small memory capacity is sufficient.

[Brief explanation of the drawing]

Fig. 1 is a claim correspondence diagram of the present invention, Fig. 2 is an explanatory diagram of the premise theory of control according to the present invention, and Fig. 3 (a) and (b) are explanatory flow charts schematically showing the configuration of the present invention. , FIG. 4 is an explanatory diagram showing the configuration of a constant speed cruise control device used to realize the application of the present invention to constant speed cruise control, and FIG. 5(a)
6(b) is an explanatory flow chart showing a constant speed running control method according to an embodiment of the present invention, and FIGS. 6(a) and 6(b) are explanatory diagrams showing examples of definitions of membership values of driving state parameters in this embodiment. , FIGS. 7(a) and 7(b) are explanatory diagrams showing examples of definitions of membership values of evaluation indicators in this embodiment, FIG. 8 is an explanatory diagram showing control laws used in this embodiment, and FIG.
Figures (a) to (d) are explanatory diagrams showing definition examples of forecast membership values for each parameter; Figure 10 is an explanatory flow chart showing the AC subroutine of the flow chart in Figure 5; (a) to (g) are explanatory diagrams showing specific examples of determining the evaluation value of the control law, FIG. 12 is an explanatory diagram showing a calculation table stored in the RAM used when determining the evaluation value, and FIG. 13 (a) and (b) are explanatory diagrams showing tables used for converting control outputs into real values, and Fig. 14 is an explanatory flowchart of an AC subroutine for constant speed driving control showing a second embodiment of the present invention. Chart, FIG. 15 is an explanatory diagram showing the control law used in the second embodiment, FIG. 16 is an explanatory diagram showing a conversion table between output commands (real values) and ambiguous labels used when searching the prediction table, FIG. 17 is an explanatory flow chart of an AC subroutine showing a third embodiment of the present invention, FIG. 18 is an explanatory diagram showing a predicted value search function used in the third embodiment, and FIG. FIG. 20 is an explanatory diagram illustrating a method for determining the evaluation value of the control law in the third embodiment. Figure 1 Figure 3 Cσ (
b) Figure 6 (a) Figure 6 (b) Figure 7 (a) Figure 7 (b) Figure 8 Figure 9 (a) Figure 9 (b) Figure 9 (C) Figure 10 Figure 11 Figure 12 Figure 13 (a) Figure 13 (b) Figure 14 Figure 15

Claims (9)

[Claims] (1) At least one parameter indicating the driving condition of the vehicle is detected or determined by a first predetermined calculation process, and the parameter is divided into a plurality of categories according to a predetermined first rule, and then at least one parameter corresponding to the category is determined. determining at least one first value, and then determining at least one second value derived according to at least one predetermined second rule based on the first value.
, and then performs a second predetermined calculation process based on the second value to obtain at least one third value, and determines the control value based on the third value. A vehicle control method characterized by: (2) The vehicle control method according to claim 1, wherein the vehicle control method is constant speed running control. (3) Claims characterized in that the parameter is any one of vehicle speed, vehicle speed acceleration, amount of change in vehicle speed acceleration per hour, or elapsed time from an inflection point of the vehicle acceleration, or a combination thereof. The vehicle control method according to item 2. (4) The first predetermined calculation process includes n-th differential of the actual measurement value;
3. The vehicle control method according to claim 2, wherein the method is addition/subtraction or proportional calculation. (5) The vehicle control method according to claim 1, wherein the first rule consists of dividing the parameter into a plurality of continuously defined sections. (6) The vehicle control method according to claim 1, wherein the second rule includes a plurality of control value calculation methods based on the first value. (7) The vehicle control method according to claim 5, wherein the control value calculation method includes a value that predicts a control result corresponding to the first value. (8) The vehicle control method according to claim 6, wherein the predicted value is an algebraic value or a set value. (9) The vehicle control method according to claim 1, wherein the second predetermined calculation process selects a maximum value of the second values.