CN108216253B - Driver type recognition control function module framework and control system of vehicle - Google Patents

Driver type recognition control function module framework and control system of vehicle Download PDF

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CN108216253B
CN108216253B CN201810011533.8A CN201810011533A CN108216253B CN 108216253 B CN108216253 B CN 108216253B CN 201810011533 A CN201810011533 A CN 201810011533A CN 108216253 B CN108216253 B CN 108216253B
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driver
accelerator
gear
module
driver factor
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CN108216253A (en
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邓涛
刘栓起
斯红路
王毅
刘增玥
银联作
黄兴
刘苏苏
习建民
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Chongqing Tsingshan Industrial Co Ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/10—Conjoint control of vehicle sub-units of different type or different function including control of change-speed gearings
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/0098—Details of control systems ensuring comfort, safety or stability not otherwise provided for
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation

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  • Automation & Control Theory (AREA)
  • Transportation (AREA)
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Abstract

The invention discloses a driver type identification control function module framework and a control system of a vehicle, which comprise a signal acquisition and processing module, an accelerator slope calculation module, an accelerator slope filtering module, a driver factor calculation module, a driver factor normalization processing module and a driver factor filtering module, wherein the signal acquisition and processing module is used for acquiring real-time engine rotating speed, accelerator and foot brake signals, vehicle speed, handle position and key switch signals; the accelerator slope calculation module is used for differentiating the accelerator to obtain an accelerator slope signal; the driver factor calculation module obtains a driver factor through the driver factor calculation module; the driver factor normalization module is used for performing normalization processing on the driver factors obtained by the driver factor calculation module; and the driver factor filtering module is used for carrying out filtering processing on the driver factor after the normalization processing to identify the type of the driver. The invention can automatically identify the type of the driver, thereby adjusting the optimal gear for the vehicle to run.

Description

Driver type recognition control function module framework and control system of vehicle
Technical Field
The invention relates to the field of automobile electronic control, in particular to a driver type identification control function module framework and a control system of a vehicle.
Background
Since the advent of Dual Clutch Transmissions (DCTs), their advantages of high transmission efficiency, compact mechanics, reliable operation, low price, etc., have been favored by various automobile manufacturers since the eighties of the last century, especially in recent years, the development of DCTs has been increasing by various automobile or transmission component suppliers, making DCTs more and more mature. DCTs are based on manual transmissions, as opposed to automatic transmissions, and provide uninterrupted power output in addition to the flexibility of manual transmissions and the comfort of automatic transmissions. Compared with the traditional manual transmission, the DCT adopts a new technology of the DCT, so that the manual transmission has automatic performance, and meanwhile, the fuel economy of an automobile is greatly improved. The DCT eliminates the torque interruption feeling of the manual transmission during gear shifting, but because of the habit of driving the vehicle by the driver, some belong to economy and some belong to power type, and the drivers of different types have different requirements on speed, while the existing DCT can not automatically identify the type of the driver, thereby being incapable of meeting the comfort level of the driver.
Disclosure of Invention
One of the objectives of the present invention is to overcome the deficiencies of the prior art, and to provide a driver type identification control function module architecture for a vehicle, which can automatically identify the type of a driver, so as to adjust the optimal gear for the vehicle to run.
It is a second object of the present invention to provide a driver type recognition control system for a vehicle, which can automatically recognize the type of a driver and adjust an optimal shift position for the vehicle to travel.
One of the purposes of the invention can be realized by the following technical scheme:
a driver type recognition control function module architecture for a vehicle, characterized in that: the system comprises a signal acquisition and processing module, an accelerator slope calculation module, an accelerator slope filtering module, a driver factor calculation module, a driver factor normalization processing module and a driver factor filtering module, wherein the signal acquisition and processing module is used for acquiring real-time engine rotating speed, accelerator and foot brake signals, vehicle speed, handle position and key switch signals; the accelerator slope calculation module is used for differentiating an accelerator to obtain an accelerator slope signal; the accelerator slope filtering module is used for filtering the accelerator slope to obtain the filtered accelerator slope; the driver factor calculation module obtains a driver factor through the driver factor calculation module according to the acquired real-time engine rotating speed, the accelerator, the foot brake, the key switch, the handle position and the vehicle speed signal; the driver factor normalization module is used for performing normalization processing on the driver factors obtained by the driver factor calculation module; and the driver factor filtering module is used for carrying out filtering processing on the driver factor after the normalization processing to identify the type of the driver.
The system further comprises a target gear calculation module, wherein the target gear calculation module adjusts the gear shifting reference speed by using the filtered driver factor and calculates the optimal gear for the vehicle to run, so that the transmission is controlled to be in the optimal gear.
The signal acquisition and processing module acquires real-time engine rotating speed, throttle and foot brake signals from the ECU through the CAN line, acquires real-time vehicle speed signals from the ABS through the CAN line, acquires real-time handle position signals from the ES L through the CAN line, and acquires key switch signals in real time.
The throttle slope filtering module adopts a first-order low-pass filter to filter the throttle slope to obtain the filtered throttle slope.
The driver factor calculation module judges whether a driver factor calculation triggering condition is met or not according to the acquired real-time engine rotating speed, an accelerator, a foot brake, a key switch, a handle position and a vehicle speed signal, and if the driver factor calculation triggering condition is met, the driver factor calculation module enters the next step, otherwise, the driver factor calculation module exits; defining input variables, including three input variables of vehicle speed v, accelerator x and accelerator slope y signals; calculating the degree of membership, determining seven degree of membership functions A (v), B (v), C (x), D (x), E (x), F (y), G (y), the membership function A (v) is that the vehicle speed is not high, the membership function B (v) is that the vehicle speed is high, the membership function C (x) is low throttle, the membership function D (x) is medium throttle, the membership function E (x) is big throttle, the membership function F (y) is medium throttle slope, the membership function G (y) is high in accelerator slope, and seven membership functions A (v), B (v), C (x), D (x), E (x), F (y) and G (y) respectively obtain 7 corresponding output values Av, Bv, Cx, Dx, Ex, Fy and Gy according to the vehicle speed v, the accelerator x and the filtered accelerator slope y; determining at least six fuzzy control rules according to the seven membership functions, wherein the six rules are subjected to fuzzy logic judgment and respectively comprise the following steps:
the 1 st fuzzy control rule is: if the vehicle speed is not high and the accelerator is moderate, the original value A1 of the driver factor is a small value of the Av and the Dx;
the 2 nd fuzzy control rule is: if the vehicle speed is not high and the throttle slope is medium, the original value A2 of the driver factor is a small value of the Av and Fy;
the 3 rd fuzzy control rule is: if the vehicle speed is not high and the slope of the accelerator is large, the original value A3 of the driver factor is a small value of the Av and the Gy;
the 4 th fuzzy control rule is: if the vehicle speed is high, the accelerator is large and the accelerator slope is large, the driver factor original value A4 is a small value of Bv, Ex and Gy;
the 5 th fuzzy control rule is that if the accelerator is small and the gradient of the accelerator is large, the original value A5 of the driver factor is a small value of Cx and Gy;
the 6 th fuzzy control rule is: the driver factor original value is balanced, and the driver factor original value A6 is 0;
defuzzification, namely performing precision processing on output obtained by fuzzy logic judgment according to the following formula to obtain a driver factor:
Figure BDA0001540483300000031
wherein A isiIs the driver factor raw value, K, of the ith fuzzy control lawnjIs a regular molecular coefficient, KdjIs a regular denominator coefficient.
The driver factor calculation triggering condition includes at least: a) electrifying a key, b) enabling a handle to be in a forward gear, c) loosening a foot brake, d) enabling the rotating speed of an engine to be greater than 400 rpm, and e) enabling the vehicle speed to be greater than 10 km/h.
The target gear calculation module adjusts the gear-shifting reference speed by using the filtered driver factor, two types of economic gear-shifting lines and motion gear-shifting lines are arranged in the target gear calculation module, and the target gear calculation module searches for the gear-shifting reference speed according to the current speed and the acceleratorFinding an economic gear shifting line to obtain an economic gear shifting reference vehicle speed VecoAnd searching a movement shift line according to the current vehicle speed and the accelerator to obtain a movement reference vehicle speed VsportSubstituting the economic gear-shifting reference speed, the motion gear-shifting reference speed and the filtered driver factor into a gear-shifting reference speed calculation formula to calculate the gear-shifting reference speed, correcting the gear-shifting reference speed in real time according to the filtered driver factor, and executing gear shifting according to the corrected gear-shifting reference speed to ensure that the vehicle runs in the best gear, wherein the gear-shifting reference speed calculation formula is as follows:
Figure BDA0001540483300000041
wherein, VrefReference vehicle speed for shifting, FdrvFor the filtered driver factor, V, of step 6ecoFor economic reference vehicle speed, VsportThe vehicle speed is referred to for movement.
The second purpose of the invention can be realized by the following technical scheme:
the driver type identification control system of the vehicle is characterized by comprising a transmission control unit, wherein the transmission control unit adopts the driver type identification control functional module framework of the vehicle.
The invention has the beneficial effects that: the invention relates to a driver type identification control function module framework of a vehicle, which identifies the type of a driver by fuzzy control logic according to three inputs of the size, the speed and the speed of stepping on an accelerator by the driver. Specifically, a driver factor is obtained by a driver factor calculation module, then the driver factor is subjected to normalization processing and filtering processing to obtain a filtered driver factor, and the type of the driver is identified according to the obtained driver factor. If the driver steps on the accelerator more quickly and the speed is not low, the driver can be considered as the type of the driver belongs to the power type, and the driver expects the vehicle to output more power; if the driver has a low accelerator and a low speed, the driver type can be considered as economical, and the vehicle is expected to output low power.
Through target gear calculation, the gear is adjusted according to the judged habit type of the driver for driving the vehicle, so that the driving speed of the vehicle is more in line with the requirement of the driver, and the vehicle is more intelligent and comfortable.
According to expert experience, the method sets six fuzzy control rules by combining the dynamic property of the vehicle and the operation of the driver, can effectively identify the type of the driver, can meet the requirements of the driver on the dynamic property or the economical property, can improve the driving pleasure of the driver, can reflect the intention of the driver more accurately, and ensures that the driver is more comfortable to drive.
Drawings
FIG. 1 is a schematic diagram of the system architecture of the present invention;
FIG. 2 is a functional block diagram of the present invention;
FIG. 3 is a block flow diagram of the driver type identification fuzzy control system module of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
The system comprises a driver type identification control function module framework of a vehicle, a signal acquisition and processing module, an accelerator slope calculation module, an accelerator slope filtering module, a driver factor calculation module, a driver factor normalization processing module and a driver factor filtering module, wherein the signal acquisition and processing module is used for acquiring real-time engine speed, accelerator and foot brake signals, vehicle speed, handle position and key switch signals, the signal acquisition and processing module acquires the real-time engine speed, accelerator and foot brake signals from an ECU (electronic control unit) through a CAN (controller area network) line, acquires the real-time vehicle speed signals from an ABS (anti-lock braking system) through the CAN line, acquires the real-time handle position signals through the CAN line and acquires the key switch signals in real time, the accelerator slope calculation module is used for acquiring accelerator slope signals by differentiating the accelerator, the accelerator slope filtering module is used for filtering the accelerator to acquire filtered accelerator slope, the slope filtering module is used for filtering the accelerator by a first-order low-pass filter to acquire the filtered accelerator slope according to the acquired real-time engine speed, accelerator, handle, and accelerator slope, the driving key, the accelerator slope filtering module is used for acquiring the accelerator slope, the accelerator slope of the accelerator slope after-pass filter, the accelerator slope calculation result of the accelerator slope calculation, the accelerator slope calculation result is that the factor after the accelerator is larger than the factor, the result is that the factor when the accelerator is larger than the factor, the factor when the speed is larger than the condition that the accelerator is larger than the condition, the condition that the accelerator is larger than the condition is:
the 1 st fuzzy control rule is: if the vehicle speed is not high and the throttle is medium, the original value of the driver factor is medium, and the original value A1 of the driver factor is a small value of Av and Dx;
the 2 nd fuzzy control rule is: if the vehicle speed is not high and the throttle slope is medium, the original value of the driver factor is medium, and the original value A2 of the driver factor is a small value of the Av and Fy;
the 3 rd fuzzy control rule is: if the vehicle speed is not high and the slope of the accelerator is large, the original value of the driver factor is high, and the original value A3 of the driver factor is a small value of the Av and the Gy;
the 4 th fuzzy control rule is: if the vehicle speed is high, the accelerator is large and the accelerator slope is large, the original value of the driver factor is high, and the original value A4 of the driver factor is a small value of Bv, Ex and Gy;
the 5 th fuzzy control rule is that if the accelerator is small and the gradient of the accelerator is large, the original value of the driver factor is high, and the original value A5 of the driver factor is a small value of Cx and Gy;
the 6 th fuzzy control rule is: the driver factor raw value is balanced and the driver factor raw value a6 is 0.
Defuzzification, namely performing precision processing on output obtained by fuzzy logic judgment according to the following formula to obtain a driver factor:
Figure BDA0001540483300000071
wherein A isiIs the driver factor raw value, K, of the ith fuzzy control lawnjIs a regular molecular coefficient, KdjIs a regular denominator coefficient.
The driver factor normalization module is used for performing normalization processing on the driver factors obtained by the driver factor calculation module; and the driver factor filtering module is used for carrying out filtering processing on the driver factor after the normalization processing to identify the type of the driver.
And the target gear calculation module adjusts the gear shifting reference speed by using the filtered driver factor and calculates the optimal gear for the vehicle to run.
The target gear calculation module adjusts the gear-shifting reference speed by using the filtered driver factor, two types of economic gear-shifting lines and moving gear-shifting lines are arranged in the target gear calculation module, and the economic gear-shifting lines are searched according to the current speed and the accelerator to obtain the economic gear-shifting reference speed VecoAnd searching a movement shift line according to the current vehicle speed and the accelerator to obtain a movement reference vehicle speed VsportSubstituting the economic gear-shifting reference speed, the motion gear-shifting reference speed and the filtered driver factor into a gear-shifting reference speed calculation formula to calculate the gear-shifting reference speed, and calculating the gear-shifting reference speed according to the filtered drivingThe driver factor corrects the gear shifting reference speed in real time, gear shifting is executed according to the corrected gear shifting reference speed, the vehicle is ensured to run on the best gear, and the gear shifting reference speed calculation formula is as follows:
Figure BDA0001540483300000081
wherein, VrefReference vehicle speed for gear shifting, VecoFor economic reference vehicle speed, VsportFor moving reference vehicle speed, FdrvIs the filtered driver factor.
Referring to fig. 3, a driver type recognition method of a vehicle includes the steps of:
the method comprises the following steps of 1, acquiring and processing signals, wherein the signals are acquired and processed and used for acquiring the rotating speed, the throttle and the foot brake signals of an engine, the vehicle speed, the handle position and the key switch signal in real time, the signals are acquired and processed through a CAN (controller area network) line from an ECU (electronic control Unit), the signals are acquired and processed through a CAN line from an ABS (anti-lock brake system), the signals are acquired and processed through a CAN line from an ES L to acquire the real-time handle position signal, and the signals are acquired and processed to acquire the key switch signal in real time, the signals are arranged in a TCU (transmission control unit), the input end of the TCU is respectively connected with the Engine Control Unit (ECU), an anti-lock brake system control unit (ABS), an electronic handle controller (ES L) and the input end of a key switch, and the information acquired.
Step 2: calculating the slope of the accelerator, wherein the slope of the accelerator is calculated by differentiating the accelerator to obtain an accelerator slope signal, and the difference value of subtracting the accelerator signal Xold of the last period (every 10 milliseconds) from the current accelerator signal Xnew is the accelerator slope in the differentiation of the accelerator;
and step 3: the system comprises an accelerator slope filtering device, a first-order low-pass filter, a second-order low-pass filter and a second-order low-pass filter, wherein the accelerator slope filtering device is used for filtering an accelerator slope to obtain a filtered accelerator slope signal;
and 4, step 4: calculating a driver factor, namely obtaining the driver factor through a driver factor calculation module according to the real-time engine rotating speed, an accelerator, a foot brake, a key switch, a handle position and a vehicle speed signal;
4.1 judging whether a driver factor calculation triggering condition is met, if so, entering the next step, and if not, exiting the identification, wherein the driver factor calculation triggering condition at least comprises the following steps: a) electrifying a key, b) enabling a handle to be positioned at a forward gear, c) loosening a foot brake, d) enabling the rotating speed of an engine to be greater than 400 revolutions per minute, and e) enabling the vehicle speed to be greater than 10 kilometers per hour;
4.2 defining input variables, adopting a fuzzy control system, and comprising three input variables of a vehicle speed v, an accelerator x and an accelerator slope y signal, wherein the value range of the accelerator slope y is-128- +127, and the vehicle speed is-128 ~ - +127
0-255(km/h), and the accelerator is 0-100 (%);
4.3. membership calculation
Determining seven membership functions of a driver type identification fuzzy control system according to expert experience, wherein the seven membership functions are A (v), B (v), C (x), D (x), E (x), F (y) and G (y) respectively, the membership function A (v) is that the vehicle speed is not high, the membership function B (v) is that the vehicle speed is high, the membership function C (x) is low throttle, the membership function D (x) is medium throttle, the membership function E (x) is big throttle, the membership function F (y) is medium throttle slope, the membership function g (y) is a high accelerator slope, and the value of each membership function is determined according to the drivability calibration of a matched vehicle, as shown in the following table, the parameters in tables 1, 2, 3, 4, 5, 6, and 7 are only one embodiment, and all the embodiments can be matched and calibrated on the whole vehicle.
The membership function a (v) is that the vehicle speed is not high, a (v) has a value range of 0-100 (because the membership value is 0-100%, but the TCU does not support floating point operation, that is, does not support decimal operation, the membership is amplified by 100 times), and a (v) has the values shown in table 1:
v 0 50 80 120 150 240
A(v) 15 15 10 0 0 0
TABLE 1
The value of A (x) is determined from the driveability calibration of the matching vehicle.
The membership function b (v) is high in vehicle speed, the value range of b (v) is 0-100 (because the membership value is 0-100%, but the TCU does not support floating-point operation, that is, does not support decimal operation, the membership is amplified by 100 times), and the value of b (v) is shown in table 2:
v 0 30 100 120 150 240
B(v) 0 0 20 20 20 20
TABLE 2
And B (v) the value is determined according to the drivability calibration of the matched vehicle.
The membership function c (x) is low, c (x) ranges from 0 to 100 (because the membership value is 0 to 100%, but TCU does not support floating-point operation, that is, decimal operation, the membership is amplified by 100 times), and c (x) is as shown in table 3:
x 0 10 20 60 80 100
C(x) 5 5 0 0 0 0
TABLE 3
And C (x) is determined according to the drivability calibration of the matched vehicle.
The membership function d (x) is throttle medium, d (x) ranges from 0 to 100 (because the membership value is 0 to 100%, but TCU does not support floating point operation, that is, decimal operation, the membership is amplified by 100 times), and d (x) is as shown in table 4:
x 0 20 40 50 60 100
D(x) 0 0 15 20 0 0
TABLE 4
And D (x) the value is determined according to the drivability calibration of the matched vehicle.
The membership function e (x) is throttle large, e (x) ranges from 0 to 100 (because the membership value is 0 to 100%, but TCU does not support floating point operation, that is, decimal operation, the membership is amplified by 100 times), and e (x) is as shown in table 5:
x 0 50 70 80 90 100
E(x) 0 0 10 20 30 30
TABLE 5
And E (x) is determined according to the drivability calibration of the matched vehicle.
The membership function f (y) is the throttle slope, f (y) ranges from 0 to 100 (because the membership value is 0 to 100%, but TCU does not support floating point operation, that is, decimal operation, the membership is amplified by 100 times), and f (y) is as shown in table 6:
y -20 0 5 10 15 20
G(y) 0 0 0 5 10 10
TABLE 6
And F (y) determining the value according to the drivability calibration of the matched vehicle.
The membership function G (y) is high in throttle slope, the value range of G (y) is 0-100 (because the membership value is 0-100%, but TCU does not support floating point operation, that is, decimal operation, the membership is amplified by 100 times), and G (y) is shown in Table 7,
y -50 0 5 10 15 30
G(y) 0 0 0 20 40 40
TABLE 7
And G (y) is determined according to the drivability calibration of the matched vehicle.
Seven membership functions A (v), B (v), C (x), D (x), E (x), F (y) and G (y) respectively obtain seven corresponding output values Av, Bv, Cx, Dx, Ex, Fy and Gy according to the vehicle speed v, the accelerator x and the filtered accelerator slope y; assuming that the vehicle speed v is 70, the accelerator x is 80, the accelerator slope y is 10, and Av is 11.67 obtained by table lookup according to the membership function a (v), the vehicle speed v is located between the a (v) axis point 50 and the point 80, the corresponding value of a (50) is 15, and the corresponding value of a (80) is 10, then Av is 15+ (70-50)/(80-50) (10-15) is 11.67 obtained by a linear interpolation method between two points. Bv, Cx, Dx, Ex, Fy, Gy, calculated similarly to the above method, gives Bv ═ 11.43, Cx ═ 0, Dx ═ 20, Ex ═ 20, Fy ═ 5, Gy ═ 20.
When the TCU runs an internal program, the method calculates the Av, the Bv, the Cx, the Dx, the Ex, the Fy and the Gy once every 10 milliseconds according to the sequence of the Av, the Bv, the Cx, the Dx, the Ex, the Fy and the Gy.
4.4 fuzzy logic judgment, determining at least six fuzzy control rules according to the seven membership functions by combining the dynamic property of the vehicle and the operation of the driver, wherein in the embodiment, six rules are adopted, and the six rules are used for fuzzy logic judgment and are respectively as follows:
the 1 st fuzzy control rule is: if the vehicle speed is not high and the throttle is medium, the driver factor original value is medium, and the driver factor original value a1 is a small value of Av and Dx (i.e., the driver factor original value a1 ═ min (Av, Dx));
the 2 nd fuzzy control rule is: if the vehicle speed is not high and the throttle slope is medium, the original value of the driver factor is medium, and the original value A2 of the driver factor is a small value of the Av and Fy;
the 3 rd fuzzy control rule is: if the vehicle speed is not high and the slope of the accelerator is large, the original value of the driver factor is high, and the original value A3 of the driver factor is a small value of the Av and the Gy;
the 4 th fuzzy control rule is: if the vehicle speed is high, the accelerator is large and the accelerator slope is large, the original value of the driver factor is high, and the original value A4 of the driver factor is a small value of Bv, Ex and Gy;
the 5 th fuzzy control rule is that if the accelerator is small and the gradient of the accelerator is large, the original value of the driver factor is high, and the original value A5 of the driver factor is a small value of Cx and Gy;
the 6 th fuzzy control rule is: the driver factor original value is balanced, and the driver factor original value A6 is 0;
7 output values Av, Bv, Cx, Dx, Ex, Fy and Gy of membership function A (v), B (v), C (x), D (x), E (x), F (y) and G (y) are input into 6 fuzzy control rules, and output values of the 6 fuzzy control rules, namely driver factor original values A1, A2, A3, A4, A5 and A6, are obtained.
4.5, the solution is defuzzified and gelatinized,
and carrying out precision processing on an output value obtained by fuzzy logic judgment according to the following accumulation average formula to obtain a driver factor:
Figure BDA0001540483300000131
wherein A isiIs the driver factor raw value, K, of the ith fuzzy control lawnjIs a regular molecular coefficient, KdjFor the coefficient of the regular denominator, here KnjAnd KdjThe test result is obtained by testing on a real vehicle.
And 5: the driver factor obtained in step 4 is normalized, and the normalization process in this embodiment maps a certain data interval to a required data interval, for example: mapping data intervals-128-127 to data intervals 0-255; the normalization processing in the patent adopts the normalization processing method in the prior art.
Step 6: and (5) filtering the driver factor subjected to the normalization processing in the step (5), wherein a first-order low-pass filter is adopted to filter the driver factor subjected to the normalization processing, and the driver is identified to be an economy or a sport type.
Further: the method also comprises a step 7 of calculating a target gear, adjusting the gear-shifting reference speed by using the filtered driver factor, setting an economic gear-shifting line and a moving gear-shifting line in a target gear calculation module, obtaining a two-dimensional table of the speed and the accelerator according to a plurality of experiments by the economic gear-shifting line according to an engine speed characteristic curve, and obtaining a two-dimensional table of the speed and the accelerator according to a plurality of experiments by the moving gear-shifting line according to an engine external characteristic and a partial load characteristic curve as shown in the following tableA two-dimensional table of vehicle speed and throttle is shown in the following table. An economic gear shifting reference speed V is obtained by searching an economic gear shifting line according to the current speed and the acceleratorecoAnd searching a movement shift line according to the current vehicle speed and the accelerator to obtain a movement reference vehicle speed VsportSubstituting the economic gear-shifting reference speed, the motion gear-shifting reference speed and the filtered driver factor into a gear-shifting reference speed calculation formula to calculate the gear-shifting reference speed, correcting the gear-shifting reference speed in real time according to the filtered driver factor, and executing gear shifting according to the corrected gear-shifting reference speed to ensure that the vehicle runs in the best gear, wherein the gear-shifting reference speed calculation formula is as follows:
Figure BDA0001540483300000141
wherein, VrefReference vehicle speed for shifting, FdrvFor the filtered driver factor, V, of step 6ecoFor economic reference vehicle speed, VsportThe vehicle speed is referred to for movement.
The target gear calculation module can obtain corresponding upshift reference vehicle speed and downshift reference vehicle speed according to the method and the current gear according to the economic upshift line and the economic downshift line of the economic shift line and the motion upshift line and the motion downshift line of the load shift line, and upshift is carried out when the vehicle speed is greater than the upshift reference vehicle speed; when the vehicle speed is less than the downshift reference vehicle speed, performing downshift; and when the vehicle speed is not greater than the upshift reference vehicle speed and not less than the downshift reference vehicle speed, maintaining the gear.
If the vehicle is in gear 1, the vehicle speed is 30km/h, the throttle is 50%, assuming a calculated filtered driver factor of 50 and a1 liter 2 economy shift line as shown in the following table:
accelerator (%) 0 10 20 30 40 50 60 80 100
Vehicle speed (km/h) 13 13 13 20 24 27 30 32 32
The 1 liter 2 sport shift line is shown in the following table:
accelerator (%) 0 10 20 30 40 50 60 80 100
Vehicle speed (km/h) 17 17 17 23 27 31 35 35 35
Then, according to the above formula and table, it can be known that: economic reference vehicle speed VecoAt 27km/h, a reference vehicle speed V of motionsport31km/h, thus obtaining a shift reference speed of 29km/h
Figure BDA0001540483300000151
At this time, the vehicle speed is 30km/h greater than the shift reference vehicle speed 29km/h, the upshift is performed, and the target gear is changed to 2.
If the vehicle is in gear 2, the vehicle speed is 18km/h, the throttle is 50%, assuming that the calculated filtered driver factor is 50, and the 2-down-1 economic shift line is as shown in the following table:
accelerator (%) 0 10 20 30 40 50 60 80 100
Vehicle speed (km/h) 8 8 8 10 14 18 22 26 26
The 2-down 1 kinematic shift lines are shown in the following table:
accelerator (%) 0 10 20 30 40 50 60 80 100
Vehicle speed (km/h) 10 10 10 12 16 20 24 28 28
Then in accordance with the aboveThe formula and the table show that: economic reference vehicle speed Veco18km/h, a movement reference vehicle speed Vsport20km/h and a shift reference vehicle speed of 19 km/h.
Figure BDA0001540483300000152
At this time, the vehicle speed is 18km/h less than the shift reference vehicle speed 19km/h, downshift is performed, and the target gear becomes 1 gear.
The method and the device can effectively identify the type of the driver, meet the requirements of the driver on the dynamic property or the economical efficiency, and improve the driving pleasure of the driver. The computer program of the driver type identification method of the vehicle of the invention is installed and operated in the transmission control unit TCU.
The invention relates to a driver type identification control system of a vehicle, which comprises a transmission control unit, wherein the transmission control unit adopts the driver type identification control functional module framework of the vehicle.

Claims (8)

1. A driver type recognition control function module architecture for a vehicle, characterized in that: the system comprises a signal acquisition and processing module, an accelerator slope calculation module, an accelerator slope filtering module, a driver factor calculation module, a driver factor normalization processing module and a driver factor filtering module, wherein the signal acquisition and processing module is used for acquiring real-time engine rotating speed, accelerator and foot brake signals, vehicle speed, handle position and key switch signals; the accelerator slope calculation module is used for differentiating an accelerator to obtain an accelerator slope signal; the accelerator slope filtering module is used for filtering the accelerator slope to obtain the filtered accelerator slope; the driver factor calculation module obtains a driver factor through the driver factor calculation module according to the acquired real-time engine rotating speed, the accelerator, the foot brake, the key switch, the handle position and the vehicle speed signal; the driver factor normalization module is used for performing normalization processing on the driver factors obtained by the driver factor calculation module; and the driver factor filtering module is used for carrying out filtering processing on the driver factor after the normalization processing to identify the type of the driver.
2. The driver type recognition control function module architecture of a vehicle according to claim 1, characterized in that: the system further comprises a target gear calculation module, wherein the target gear calculation module adjusts the gear shifting reference speed by using the filtered driver factor and calculates the optimal gear for the vehicle to run, so that the transmission is controlled to be in the optimal gear.
3. The vehicle driver type recognition control function module architecture of claim 1, wherein the signal acquisition and processing module acquires real-time engine speed, throttle and foot brake signals from the ECU through the CAN line, real-time vehicle speed signals from the ABS through the CAN line, real-time handle position signals from the ES L through the CAN line, and key switch signals in real time.
4. The driver type recognition control function module architecture of a vehicle according to claim 1, characterized in that: the throttle slope filtering module adopts a first-order low-pass filter to filter the throttle slope to obtain the filtered throttle slope.
5. The driver type recognition control function module architecture of a vehicle according to claim 1, characterized in that: the driver factor calculation module judges whether a driver factor calculation triggering condition is met or not according to the acquired real-time engine rotating speed, an accelerator, a foot brake, a key switch, a handle position and a vehicle speed signal, and if the driver factor calculation triggering condition is met, the driver factor calculation module enters the next step, otherwise, the driver factor calculation module exits; defining input variables, including three input variables of vehicle speed v, accelerator x and accelerator slope y signals; calculating the degree of membership, determining seven degree of membership functions A (v), B (v), C (x), D (x), E (x), F (y), G (y), the membership function A (v) is that the vehicle speed is not high, the membership function B (v) is that the vehicle speed is high, the membership function C (x) is low throttle, the membership function D (x) is medium throttle, the membership function E (x) is big throttle, the membership function F (y) is medium throttle slope, the membership function G (y) is high in accelerator slope, and seven membership functions A (v), B (v), C (x), D (x), E (x), F (y) and G (y) respectively obtain 7 corresponding output values Av, Bv, Cx, Dx, Ex, Fy and Gy according to the vehicle speed v, the accelerator x and the filtered accelerator slope y; determining at least six fuzzy control rules according to the seven membership functions, and carrying out fuzzy logic judgment on the six fuzzy control rules respectively as follows:
the 1 st fuzzy control rule is: if the vehicle speed is not high and the accelerator is moderate, the original value A1 of the driver factor is a small value of the Av and the Dx;
the 2 nd fuzzy control rule is: if the vehicle speed is not high and the throttle slope is medium, the original value A2 of the driver factor is a small value of the Av and Fy;
the 3 rd fuzzy control rule is: if the vehicle speed is not high and the slope of the accelerator is large, the original value A3 of the driver factor is a small value of the Av and the Gy;
the 4 th fuzzy control rule is: if the vehicle speed is high, the accelerator is large and the accelerator slope is large, the driver factor original value A4 is a small value of Bv, Ex and Gy;
the 5 th fuzzy control rule is that if the accelerator is small and the gradient of the accelerator is large, the original value A5 of the driver factor is a small value of Cx and Gy;
the 6 th fuzzy control rule is: the driver factor original value is balanced, and the driver factor original value A6 is 0;
defuzzification, namely performing precision processing on output obtained by fuzzy logic judgment according to the following formula to obtain a driver factor:
Figure FDA0002457291800000031
wherein A isiIs the driver factor raw value, K, of the ith fuzzy control lawnjIs a regular molecular coefficient, KdjIs a regular denominator coefficient.
6. The driver type recognition control function module framework of a vehicle according to claim 1, characterized in that: the driver factor calculation triggering condition includes at least: a) electrifying a key, b) enabling a handle to be in a forward gear, c) loosening a foot brake, d) enabling the rotating speed of an engine to be greater than 400 rpm, and e) enabling the vehicle speed to be greater than 10 km/h.
7. The driver type recognition control function module framework of a vehicle according to claim 2, characterized in that: the target gear calculation module adjusts the gear-shifting reference speed by using the filtered driver factor, two types of economic gear-shifting lines and moving gear-shifting lines are arranged in the target gear calculation module, and the economic gear-shifting lines are searched according to the current speed and the accelerator to obtain the economic gear-shifting reference speed VecoAnd searching a movement shift line according to the current vehicle speed and the accelerator to obtain a movement reference vehicle speed VsportSubstituting the economic gear-shifting reference speed, the motion gear-shifting reference speed and the filtered driver factor into a gear-shifting reference speed calculation formula to calculate the gear-shifting reference speed, correcting the gear-shifting reference speed in real time according to the filtered driver factor, and executing gear shifting according to the corrected gear-shifting reference speed to ensure that the vehicle runs in the best gear, wherein the gear-shifting reference speed calculation formula is as follows:
Figure FDA0002457291800000041
wherein, VrefReference vehicle speed for shifting, FdrvAs filtered driver factor, VecoFor economic reference vehicle speed, VsportThe vehicle speed is referred to for movement.
8. A driver type recognition control system of a vehicle, characterized by comprising a transmission control unit employing a driver type recognition control function module framework of a vehicle according to any one of claims 1 to 7.
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