Locomotive and weighted parameter adhesion control method therefor

Abstract

A locomotive and a weighted parameter adhesion control method therefor. The method comprises: according to an operation state of a locomotive, acquiring a traction electric motor torque given value and a weighted adhesion control reference value, to generate a traction electric motor torque given control value; calculating a weighted adhesion control feedback value; performing calculation, in a weighted adhesion control PI closed-loop controller, with the weighted adhesion control reference value and the weighted adhesion control feedback value, so as to obtain a weighted adhesion control value; controlling the torque of a traction electric motor according to the smaller of the weighted adhesion control value and the traction electric motor torque given control value; and from a moment T0, filtering the traction electric motor torque given value according to m*G(S) until the traction electric motor torque given control value is recovered to a% of the maximum torque value of the traction electric motor, and then carrying out filtering processing on the traction electric motor torque given value according to G(S) / n. According to the method, the adhesion force of the locomotive is exerted to the maximum extent, and traction idling or braking coasting is effectively prevented, such that the locomotive exerts the maximum traction force or braking force under the current rail surface condition.

Description

Locomotive and weighted parameter adhesion control method thereof TECHNICAL FIELD The present disclosure relates to the technical field of electric traction and transmission control of railway locomotives, and in particular to a locomotive and a weighted parameter adhesion control method thereof. BACKGROUND OF THE INVENTION High-speed railway and heavy-duty transportation are important signs of railway modernization. In order to achieve the goal of high-speed and heavy-duty, it is very important to maximize the exertion of the traction and braking performance of the locomotive, and the utilization situation of wheel-rail adhesion directly affects the exertion of the traction and braking performance of the locomotive. When the wheel traction or braking force generated by the wheelset is greater than the adhesion force between the wheel-rails, the wheel will idle or slip, so that the traction force or braking force is drastically reduced, and wheel-rail heating and wheel-rail scratches will be occurred. In severe cases, it will also affect the safe operation of the locomotive and cause great harm. The adhesion between the wheel-rails is a complex time-varying system with uncertainty, and a specific control method is required to effectively prevent the traction idling or the braking sliding, and make the locomotive exert the maximum traction force or braking force under the current rail surface state. In the field of anti-idling sliding and adhesion control of the locomotive, the commonly used schemes include differential relay method, threshold method, multi-parameter combined control method, stability enhancement control method and so on. However, these control methods are focused on the identification of idling and sliding and the active load reduction strategies. It is difficult to select the appropriate load reduction time, percentage of load reduction rate, and load reduction duration, and it is difficult to maximize the exertion of adhesion force. Specifically, in an existing control method, the acceleration of the locomotive wheelset is detected in real time, the torque is started to unloaded when the acceleration exceeds the protection threshold, and the acceleration peak is continuously searched during the unloading process, until the acceleration peak is detected, and the unloading of the torque is immediately stopped, such that the adhesion of the locomotive wheelset is restored. This method is based on the real-time detection of the operating speed of the locomotive, and takes the acceleration of the locomotive wheelset exceeding a certain threshold as the entry point to implement locomotive load reduction measures. Under normal conditions of speed sensors of the locomotive, this method is very suitable, but when the sensor fails, it is judged that it is idling and sliding only by the single-axis speed and acceleration, which will causes misjudgment, and reduces the traction of the locomotive due to misjudgment and affects the operation of the locomotive. Based on this, the prior art still needs to be improved. SUMMARY OF THE INVENTION In order to solve the above technical problems, the embodiment of the present disclosure proposes a locomotive and a weighted parameter adhesion control method thereof. The present disclosure solves the technical problem that the adhesive force of the prior art cannot be exerted to the maximum, the utilization of wheel-rail adhesive force is maximized, and the traction idling or brake sliding is effectively prevented. A weighted parameter adhesion control method disclosed in an embodiment of the present disclosure, comprising: Step 1: according to an operating state of a locomotive, obtaining the traction motor torque given value Tqref by querying the traction / electric braking torque characteristic curve, and generating the traction motor torque given control value Tqrefout via a first-order low-pass filter with a transfer function of G(S), and Tqrefout is limited by a maximum and a minimum, that is to say, Tqmin<Tqrefout<< Tqmax; Step 2: according to the operating state of the locomotive, obtaining a weighted adhesion control reference value TqAdref by querying the traction / electric braking weighted adhesion control reference value curve; Step 3: calculating a weighted adhesion control feedback value TqAdfdb based on weighted adhesion control feedback factors Adivl, Adiv2, and Adiv3 according to the following formula: TqAdfdb=Adiv1+Adiv2+Adiv3; Step 4: utilizing the weighted adhesion control reference value TqAdref and the weighted adhesion control feedback value TqAdfdb to obtain a weighted adhesion control value TqAdout in a weighted adhesion control PI closed-loop controller TqAd, and TqAdout is limited by a maximum and a minimum, that is to say, Tqmin< TqAdout<Tgmax; Step 5: controlling a traction motor torque Tqout according to the smaller one of the weighted adhesion control value TqAdout and the traction motor torque given control value Tqrefout; and Step 6: when TqAdout<Tqrefout, setting Tqrefout=TqAdout, and recording the maximum value Tqoutmax of Tqout in the first Ts seconds of time TO; starting from the time TO, filtering the traction motor torque given value Tqref via a first-order low-pass filter with a transfer function of m*G(S), until Tqrefout is restored to a% of Tqoutmax, and then filtering the traction motor torque given value Tqref via a first-order low-pass filter with a transfer function of G(S) / n, until Tqrefout is equal to Tqref; wherein, 1<m<10; 1<n<10. During the operation of the locomotive, the above steps are performed periodically. According to an embodiment of the present disclosure, the operating state of the locomotive comprises at least one of a traction / electric braking instruction, a handle level and a traction motor speed. According to an embodiment of the present disclosure, the transfer function G(S) is: G(s) = Le sto, wherein, k is a gain, © isa angular frequency. According to an embodiment of the present disclosure, the step 2 further comprises: monitoring a state of a speed sensor of a traction motor in real time, detecting and correcting speed signals RPM[i](i=1,2...n) of the current effective speed sensors of the traction motor, wherein n is the number of axles of the locomotive, calculating an average speed value RPMav of the traction motor, a maximum speed value RPMmax of the traction motor, and a minimum speed value RPMmin of the traction motor in the whole locomotive, calculating an average speed value RPMTav of the traction motor, a maximum speed value RPMTmax of the traction motor, and a minimum speed value RPMTmin of the traction motor in each bogie, calculating a body-to-ground conversion speed estimated value RPMg. Specifically, the step 2 further comprises: 1) detecting the actual speed RPMR[i] (i=1,2...n) of the traction motor of each axle, wherein n is the number of axles of the locomotive, and calculating the actual average speed RPMRav of the traction motor of each axle; 2) detecting the actual current AMP[i] (i=1,2...n) of the traction motor of each axle, wherein n is the number of axles of the locomotive, calculating the average current AMPav of the traction motor of each axle; 3) when satisfying RPMRav>=RPMRLow, and RPMR[i]<=k1*RPMRav, and AMP[i]<k2*AMPav, after a delay of t1 seconds, it is judged that the i-th speed sensor of the traction motor fails, and the failure is automatically cleared after the control system is powered on again, wherein the parameter RPMRLow is generally selected as the traction motor speed corresponding to the locomotive speed of 3km / h, ki is generally selected as a real number between 0.6-0.9, k2 is generally selected as a real number between 1.1-1.25; 4) after filtering the speed signal RPMR[i] of the axles position without the the speed sensor failure via a first-order low-pass filter and after checking the wheel diameter, the speed signal RPM([i] of the effective speed sensor of the traction motor is obtained, and the RPM[i] is accumulated and the accumulated result is divided by the number of axles without the the speed sensor failure to obtain the average speed value RPMav of the traction motor, each RPM[i] are compared in which the maximum value is RPMmax and the minimum value is RPMmin; RPM[i] of each bogie are compared in which the maximum value is RPMTmax and the minimum value is RPMTmin, and meanwhile the average speed value RPMTav of the traction motor of each bogie is calculated; 5) performing a constant slope filtering processing on RPMav to obtain the body-to-ground conversion speed estimated value RPMg: in the traction state, if RPMg+AN<RPMav, then RPMg=RPMg+AN, otherwise RPMg=RPMav; in the electric braking state, if RPMg>RPMav+AN, then RPMg=RPMg-AN, otherwise RPMg=RPMav; wherein, AN is the corresponding wheelset speed when the locomotive is operating at a maximum acceleration of 2Km / h / s in one execution cycle, and the unit is revolutions per second. If the locomotive is equipped with a radar speed measuring device, the value of RPMg is directly obtained from the radar speed measurement signal; and if the locomotive is equipped with a non-power axle speed measuring device, the value of RPMg is directly obtained from the non-power axle speed measurement signal. According to an embodiment of the present disclosure, the body-to-ground conversion speed estimated value RPMg is obtained by a radar speed measuring device or a non-power axle speed measuring device. According to an embodiment of the present disclosure, the adhesion control feedback factors is obtained according to the following formula: Adivl=31*AdF1, Adiv2=52*AdF2, Adiv3=383*AdF3, wherein, 31, 32, and 33 are weighting coefficients greater than 1 and less than 5, AdF1 is a transient acceleration / deceleration feedback parameter, AdF2 is a speed difference feedback parameter, and AdF3 is a acceleration limit feedback parameter. According to an embodiment of the present disclosure, in step 4, the transfer function adopted by the weighted adhesion control PI closed-loop controller TqAd is TqAdout = TqAdout + Kp[e(k)-e(k-1)]+Ki*e(k), wherein, Kp and Ki are a proportional parameter and an integral parameters of the PI closed-loop controller TqAd, e(k) is a difference between TqAdref and TqAdfdb at this time, e(k-1) is a difference between the TqAdref and TqAdfdb at the previous time. That is, starting from the time TO, the traction motor torque given value Tqref is filtered until Tqrefout is restored to a% of Tqoutmax, the Kp and Ki are respectively increased to a times of the original Kp and Ki parameters. According to an embodiment of the present disclosure, in step 4, when the difference between the weighted adhesion control feedback value TqAdfdb and the weighted adhesion control reference value TqAdref is greater than B*TqAdref (0.5<p<1) , the control system performs a sanding instruction of the corresponding axle position. According to an embodiment of the present disclosure, the AdF1, AdF2 and AdF3 are calculated in the manner of locomotive control, bogie control and axle control. Specifically, when the motor control adopts the locomotive control mode, the transient acceleration (deceleration) speed feedback parameter AdF1 is the difference between the average speed value RPMav (tk) of the traction motor of the whole locomotive at this sampling point and the average speed value RPMav (tk-1) of the traction motor of the whole locomotive at the previous sampling point (traction condition), or is the difference between the average speed value RPMav(tk-1) of the traction motor of the whole locomotive at the previous sampling point and the average speed value RPMav(tk)of the traction motor of the whole locomotive at this sampling point (electric braking condition), if the difference is less than zero, then AdF1 takes zero; the speed difference feedback parameter AdF2 is the difference between the maximum speed RPMmax of the traction motor of the whole locomotive and the average speed RPMav of the traction motor of the whole locomotive (traction condition) or is the difference between the average speed RPMav of the whole locomotive and the minimum speed RPMmin of the whole locomotive (electric braking condition), if the difference is less than zero, then AdF2 takes zero; the acceleration limit feedback parameter AdF3 is the difference between the average speed RPMav of the whole locomotive and the body-to-ground conversion speed estimated value RPMg (traction condition) or is the difference between the body-to-ground conversion speed estimated value RPMg and the average speed RPMav of the whole locomotive (electric braking condition) , if the difference is less than zero, then AdF3 takes zero. When the motor control adopts the bogie control mode, the front and rear bogies are calculated separately. When the calculated bogie is the front bogie, the transient acceleration (deceleration) speed feedback parameter AdF1 is the difference between the average speed value RPFav (tk) of the traction motor of the front bogie at this sampling point and the average speed value RPMFav (tk-1) of the traction motor of the front bogie at the previous sampling point (traction condition), or the difference between the average speed value RPMFav (tk-1) of the traction motor of the front bogie at the previous sampling point and the average speed value RPFav (tk) of the traction motor of the front bogie at this sampling point (traction condition), if the difference is less than zero, then AdF1 takes zero; the speed difference feedback parameter AdF2 is the difference between the maximum speed RPMFmax of the traction motor of the front bogie and the average speed RPMav of the traction motor of the whole locomotive (traction condition) or is the difference between the average speed RPMav of the traction motor of the whole locomotive and the minimum speed RPMFmin of the front bogie (electric braking condition), if the difference is less than zero, then AdF2 takes zero; the acceleration limit feedback parameter AdF3 is the difference between the average speed RPMFav of the front bogie and the body-to-ground conversion speed estimated value RPMg (traction condition) or is the difference between the body-to-ground conversion speed estimated value RPMg and the average speed RPMFav of the front bogie (electric braking condition), if the difference is less than zero, then AdF3 takes zero. Similarly, when the calculated bogie is the rear bogie, the transient acceleration (deceleration) speed feedback parameter AdF1 is the difference between the average speed value RPBav (tk) of the traction motor of the rear bogie at this sampling point and the average speed value RPMBav (tk-1) of the traction motor of the rear bogie at the previous sampling point, if the difference is less than zero, then AdF1 takes zero; the speed difference feedback parameter AdF2 is the difference between the maximum speed RPMBmax of the traction motor of the rear bogie and the average speed RPMav of the traction motor of the whole locomotive (traction condition) or is the difference between the average speed RPMav of the traction motor of the whole locomotive and the minimum speed RPMBmin of the rear bogie (electric braking condition), if the difference is less than zero, then AdF2 takes zero; the acceleration limit feedback parameter AdF3 is the difference between the average speed RPMBav of the rear bogie and the body-to-ground conversion speed estimated value RPMg (traction condition) or is the difference between the body-to-ground conversion speed estimated value RPMg and the average speed RPMBav of the rear bogie (electric braking condition), if the difference is less than zero, then AdF3 takes zero. When the motor control adopts the axle control mode, each axle is calculated separately. The transient acceleration (deceleration) speed feedback parameter AdF1 is the absolute value of the difference between the speed value RPM[i](tk) of traction motor of the current axle at this sampling point and the speed value RPM[i](tk-1) of the traction motor of the current axle at the previous sampling point, if the difference is less than zero, then AdF1 takes zero; the speed difference feedback parameter AdF2 is the difference between the speed RPM[i] of the traction motor of the current axle and the speed average value RPMav of the traction motor of the whole locomotive (traction conditions) or is the difference between the speed average value RPMav of the traction motor of the whole locomotive and the speed RPMJi] of the traction motor of the current axle (electric braking condition), if the difference is less than zero, then AdF2 takes zero; the acceleration limit feedback parameter AdF3 is the difference between the speed RPMI] of thetraction motor of the current axle and the body-to-ground conversion speed estimated value RPMg (traction condition), or the difference between the body-to-ground conversion speed estimated value RPMg and the speed RPM] of the traction motor of the current axle (electric braking condition) , if the difference is less than zero, AdF3 takes zero. The present disclosure also discloses a locomotive which adopts the above-mentioned weighted parameter adhesion control method. With the above technical solutions, the present disclosure at least has the following beneficial effects: the invention determines the optimal load reduction time, percentage of load reduction rate and load reduction duration by comprehensively judging the multiple operating parameters of the locomotive, so as to maximize the exertion of adhesion forces of the locomotive, effectively prevent the traction idling or braking sliding, and make the locomotive exert the maximum traction or braking force under the current rail surface state. BRIEF DESCRIPTION OF THE DRAWINGS In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced in the following. Obviously, the drawings in the following description are only some embodiments of the present disclosure. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. FIG. 1 is a flowchart of the main program of an embodiment of the present disclosure. FIG. 2 is a flowchart of a program for calculating a speed related value according to an embodiment of the present disclosure. FIG. 3 is a flowchart of a subroutine for calculating the weighted adhesion control feedback value TqAdfdb according to an embodiment of the present disclosure. FIG. 4 is a flowchart of the subroutines of AdF1, AdF2, and AdF3 in the bogie control mode of the embodiment of the present disclosure. FIG. 5 is a flowchart of the subroutines of AdF1, AdF2, and AdF3 in the axle control mode of the embodiment of the present disclosure. DETAILED DESCRIPTION In order to make the object, technical solutions, and advantages of the present disclosure clearer, the embodiments of the present disclosure will be further described in detail below in conjunction with specific embodiments and with reference to the drawings. It should be noted that all the expressions using "first" and "second" in the embodiments of the present disclosure are used to distinguish two entities with the same name but not the same entities or parameters, it can be seen that "first" and "second" are only for convenience of expression, and should not be construed as limiting the embodiments of the present disclosure, and subsequent embodiments will not be described one by one. As shown in FIG.1, the embodiment of the present disclosure discloses a main program flowchart of a weighted parameter adhesion control method. The corresponding software of this flowchart is invoked periodically (generally 10-20ms). Firstly, according to the operating state of the locomotive, obtain a traction motor torque given value Tqref by querying the traction / electric braking torque characteristic curve, and generate the traction motor torque given control value Tqrefout via a first-order low-pass filter with a transfer function of G(S), and Tqrefout is limited by a maximum and a minimum, that is to say, Tqmin<Tqrefout<<Tqmax, as a reference value given by the motor torque in the traction / electric braking condition of the locomotive; secondly, obtain a weighted adhesion control reference value TqAdref and a weighted adhesion control feedback value TqAdfdb according to the operating state of the locomotive, and put the weighted adhesion control reference value TqAdref and the weighted adhesion control feedback value TqAdfdb into the weighted adhesion control PI closed-loop controller TgAd to obtain the weighted adhesion control value TqAdout, and TqAdout is limited by a maximum and a minimum, that is to say, Tqmin< TqAdout<<Tqmax, as another reference value given by motor torque in the traction / electric braking condition of the locomotive; then, comparing Tqrefout with TqAdout, and controlling the traction motor torque Tqout based onthe smaller one of the both. When TqAdout<Tqgrefout, setting Tgrefout=TqAdout, and recording the maximum value Tqoutmax of Tqout in the first Ts of time TO. Starting from TO, filtering the traction motor torque given value Tqref via a first-order low-pass filter with a transfer function of m*G(S) until Tqrefout is restored to a% of Tqoutmax, and then filtering the traction motor torque given value Tqref via a first-order low-pass filter with a transfer function of G(S) / n until Tqrefout is equal to Tqref. In the present disclosure, in order to realize the closed-loop control of the adhesion of the locomotive, the key is to construct the weighted adhesion control PI closed-loop controller TqAd. Therefore, the weighted adhesion control reference value curve is designed in the software, and the traction / electric braking weighted adhesion control reference value curve can be inquired in real time to obtain the weighted adhesion control reference value TqAdref according to the traction / electric braking instructions , the handle level, the traction motor speed and other parameters on instructions and states, TqAdref is the given value of the PI closed-loop controller TqAd obtained by weighted addition of multiple parameters. In the process of calculating the weighted adhesion control feedback value TqAdfdb, the first step is to detect and correct the current effective speed RPM[i] of the traction motor, and calculate other related speed values. The program flow chart is shown in Figure 2Calculate the average speed RPMRav of the whole locomotive from the detected current effective speed RPM[i] of the traction motor. And detecte the actual current AMPJ[i] of the traction motor of each axle, and calculate the average current AMPav of the traction motor. The validity of the speed sensor of the traction motor is judged axle by axle, and the judgment conditions are as follows: when RPMRav>=RPMRLow (RPMRLow is generally selected as the speed of the traction motor corresponding to the locomotive speed of 3km / h) and RPMR[i]<=k1*RPMRav and AMP[i]<k2*AMPav are satisfied, the i-th speed sensor of the traction motor is determined to fail after a delay of tI seconds, wherein: kl is generally selected as a real number between 0.6 and 0.9, and k2 is generally selected as a real number between 1.1 and 1.25. The number of axles with speed sensor failure is marked, and the number Sn of the axles without speed sensor failure in the whole locomotive, the number SFn of the axles without speed sensor failure in the front bogie, and the number SBn of the axles without speed sensor failure in the rear bogie are calculated. After filtering the speed signal RPMR[i] of the axle position without the speed sensor failure via the first-order low-pass filter, and after checking the wheel diameter, the effective speed signal RPM[i] of the speed sensor of the traction motor is obtained. The RPMJi] is accumulated and the accumulated result is divided by the number Sn of the axles without speed sensor failure to obtain the average speed value RPMav of the traction motor. The RPM[i] are compared in which the maximum value is RPMmax and the minimum value is RPMmin. The RPM[i] of the traction motor of the front bogie are accumulated and the accumulated result is divided by the number SFn of axles without speed sensor failure in the front bogie to obtain the average speed value RPMFav of the traction motor of the front bogie, the RPM [i] of the traction motor of the front bogie are compared in which the maximum value is RPMFmax, and the minimum value is RPMFmin; the average speed value RPMBav of the traction motor of the rear bogie is obtained according to the same principle, the maximum speed value of the traction motor of the rear bogie is RPMBmax, and the minimum speed value of the traction motor of the rear bogie is RPMBmin. The RPMav is filtered with a constant slope to obtain the estimated body-to-ground conversion speed value RPMg: in the traction state, if RPMg+tAN<RPMav, then RPMg= RPMg+AN, otherwise RPMg=RPMav; in the electric braking state, if RPMg>RPMav+AN, then RPMg=RPMg-AN, otherwise RPMg=RPMav. If the locomotive is equipped with a radar speed measuring device, the value of RPMg is directly obtained from the radar speed measurement signal; if the locomotive is equipped with a non-power axle speed measuring device, the value of RPMg is directly obtained from the non-power axle speed measurement signal. The program flow chart for calculating the weighted adhesion control feedback value TqAdfdb is shown in Figure 3. The process needs to consider the control modes of the traction system of the locomotive: locomotive control, bogie control, and axle control. If the locomotive control mode is adopted, first it is judged that whether the locomotive is in traction condition or braking condition. When the locomotive is in traction condition, and when the average speed value RPMav of the traction motor of the locomotive in current time is greater than the average speed value RPMavLast of the traction motor in the previous cycle, AdF1=RPMav-RPMavLast,otherwise AdF1 is zero; when the maximum speed value RPMmax of the traction motor is greater than the average speed value RPMav of the traction motor: AdF2=RPMmax-RPMav, otherwise AdF2 is zero; when the average speed value RPMav of the traction motor is greater than the estimated body-to-ground conversion speed value RPMg: AdF3=RPMav-RPMg, otherwise AdF3 is zero. When the locomotive is in the braking condition, and when the average speed value RPMav of the traction motor of the locomotive in current time is less than the average speed value RPMavLast of the traction motor in the previous cycle, AdF1=RPMavLast-RPMav, otherwise AdF1 is zero; when the minimum speed value RPMmin of the traction motor is less than the average speed value RPMav of the traction motor: AdF2=RPMav-RPMmin, otherwise AdF2 is zero; when the average speed value RPMav of the traction motor is less than the estimated body-to-ground conversion speed value RPMg: AdF3=RPMg-RPMav, otherwise AdF3 is zero. If the bogie control mode is adopted, the flow chart of the AdF1, AdF2, and AdF3 subroutines is shown in Figure 4, in which: jmax is the number of bogies of the locomotive, which needs to be cyclically judged. When the locomotive is in traction mode, it is judged that whether the average speed value RPMTav[j](j=1,...jmax)of the traction motor of the bogie in current time is greater than the average speed value RPMTavLast[j](j=1,...jmax)of the traction motor of the bogie in the previous cycle , if RPMTav[j]>RPMJavLast[j],then AdF1=RPMTav[j]-RPMJavLast[j], otherwise AdF1 is zero; it is judged that whether the maximum speed value RPMTmax[j](j=1,...jmax) of the traction motor of the bogie is greater than the average speed value RPMav of the traction motor of the whole locomotive, if RPMTmax[j]>RPMav, then AdF2=RPMTmax[j]-RPMav, otherwise AdF2 is zero; it is judged that whether the average speed value RPMTav([j](j=1,...jmax) of the traction motor of the bogie is greater than the estimated body-to-ground conversion speed value RPMg, if RPMTav[j]>RPMg, then AdF3=RPMTav[j]-RPMg, otherwise AdF3 is zero. When the locomotive is in the braking mode, it is judged whether the average speed value RPMTav[j](j=1,...jmax)of the traction motor of the bogie in current time is less than the average speed value RPMTavLast[j](j= 1,...jmax)of the traction motor of the bogie in the previous cycle, if RPMTav[j]<RPMJavLast[j], then AdF1=RPMJavLast[j]-RPMTav[j], otherwise AdF1 is zero; it is judged whether the minimum speed value RPMTmin[j](j =1,...jmax) of the traction motor of the bogie is less than the average speed value RPMav of the traction motor of the whole locomotive, if RPMTmin[jJ<RPMav, then AdF2=RPMav-RPMTmin[j], otherwise AdF2 is zero; it is judged whether the average speed value RPMTav [j](j=1,..jmax) of the traction motor of the bogie is less than the estimated body-to-ground conversion speed value RPMg, if RPMTav[j]<RPMg, then AdF3=RPMg-RPMTav[j], otherwise AdF3 is zero. If the axle control mode is adopted, the flow chart of the AdF1, AdF2, and AdF3 subroutines is shown in Figure 5, in which: imax is the number of axles of the locomotive , which needs to be cyclically judged. When the locomotive is in traction mode, it is judged whether the speed signal RPM[i](i=1,2...imax) of the effective speed sensor of the traction motor in current time is greater than the speed signal RPMLast[i](i=1,2...imax) of the effective speed sensor of the traction motor of the axle in the previous cycle, if RPM[i]>RPMLast[i], then AdF1=RPM[i]-RPMLast[i], otherwise AdF1 is zero; it is judged whether speed sensor speed signal RPMav RPM[i](i=1,2...imax) of the effective speed sensor of the traction motor in cuurent time is greater than the average speed value RPMav of the traction motor of the whole locomotive, if RPM[i]>RPMav, AdF2=RPM[i]-RPMav, otherwise AdF2 is zero; it is judged whether the speed signal RPM[i](i= 1,2...imax) of the effective speed sensor of traction motor in current time is greater than the estimated body-to-ground conversion speed value RPMg, if RPM[i]>RPMg, then AdF3=RPM[i]-RPMg, otherwise AdF3 is zero. If the locomotive is in the braking mode, it is judged whether speed signal RPM[i](i=1,2...imax)of the effective speed sensor of the traction motor in current time is less than the speed singal RPMLast[i] (i=1,2...imax) of the effective speed sensor of the traction motor in the previous cycle, if RPM[i]J<RPMLast[i], then AdF1=RPMLast[i]-RPM][i], otherwise AdF1 is zero; it is judged whether the speed signal RPM [i](i=1,2...imax) of the effective speed sensor of the traction motor in current time is less than the average speed value RPMav of the traction motor of the whole locomotive , if RPM[i]<RPMav, then AdF2=RPMav-RPM[i], otherwise AdF2 is zero; it is judged whether the speed signal RPM[i] (i=1,2...imax) of the effective speed sensor of the traction motor in current time is less than the estimated body-to-ground conversion speed value RPMg, if RPMJ[i]J<RPMg, then AdF3=RPMg-RPM[i], otherwise AdF3 is zero. The parameter values of AdF1, AdF2, and AdF3 obtained by the above calculation are multiplied by their respective weighting coefficients 31, 82, and 33 (weighting coefficients greater than 1 and less than 5) to obtain the weighted adhesion control feedback value TqAdfdb=51*AdF1+52*AdF2+63*AdF3. It should be particularly pointed out that the various components or steps in the above embodiments can be crossed, replaced, added, or deleted. Therefore, the combination formed by these reasonable permutations and transformations should also belong to the protection scope of the present disclosure and the protection scope of the present disclosure should not be limited to the described embodiments. The foregoing are exemplary embodiments disclosed in the present disclosure. The sequence disclosed in the foregoing embodiments of the present disclosure is only for description, and does not represent the superiority of the embodiments. However, it should be noted that the discussion of any of the above embodiments is only exemplary, and is not intended to imply that the scope (including the claims) disclosed by the embodiments of the present disclosure is limited to these examples, various changes and modifications can be made without departing from the scope defined by the claims. The functions, steps and / or actions of the method claims according to the disclosed embodiments described herein do not need to be executed in any specific order. In addition, although the elements disclosed in the embodiments of the present disclosure may be described or required in individual forms, they may also be understood as plural unless explicitly limited to a singular number. Those of ordinary skill in the art should understand that the discussion of any of the above embodiments is only exemplary, and is not intended to imply that the scope of disclosure (including the claims) of the embodiments of the present disclosure is limited to these examples; under the idea of the embodiments of the present disclosure, the above embodiments or the technical features in different embodiments can also be combined, and there are many other changes in different aspects of the embodiments of the present disclosure as described above, which are not provided in the details for brevity. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the embodiments of the present disclosure should be included in the protection scope of the embodiments of the present disclosure.

Claims

Claims:

1. A weighted parameter adhesion control method, characterized in that, comprising: Step 1: obtaining a traction motor torque given value Tqref according to an operating state of a locomotive, and generating a traction motor torque given control value Tqrefout based on the obtained traction motor torque given value Tqref and a transfer function G(S); Step 2: obtaining a weighted adhesion control reference value TqAdref according to the operating state of the locomotive; Step 3: calculating a weighted adhesion control feedback value TqAdfdb based on weighted adhesion control feedback factors Adivl, Adiv2, and Adiv3 according to the following formula: TqAdfdb=Adivl+Adiv2+Adiv3; Step 4: utilizing the weighted adhesion control reference value TqAdref and the weighted adhesion control feedback value TqAdfdb to obtain a weighted adhesion control value TqAdout in a weighted adhesion control PI closed-loop controller TqAd; Step 5: controlling a traction motor torque Tqout according to the smaller one of the weighted adhesion control value TqAdout and the traction motor torque given control value Tgrefout; and Step 6: when TqAdout<Tqrefout, setting Tqrefout=TqAdout, and recording the maximum value Tqoutmax of Tqout within the first Ts seconds of time TO; starting from the time TO, filtering the traction motor torque given value Tqref via a first-order low-pass filter with a transfer function of m*G(S), until Tqrefout is restored to a% of Tqoutmax, and then filtering the traction motor torque given value Tqref via a first-order low-pass filter with a transfer function of G(S) / n, until Tqrefout is equal to Tqref; wherein, 1<m<10; 1<n<10.

2. The method of claim 1, characterized in that, the operating state of the locomotive comprises at least one of a traction / electric braking instruction, a handle level and a traction motor speed.

3. The method of claim 1, characterized in that, the transfer function G(S) is: G(s) =k—2 sto. wherein, k is a gain, @ is a cut-off angular frequency.

4. The method of claim 1, characterized in that, the step 2 further comprises: monitoring a state of a speed sensor of a traction motor in real time, detecting and correcting speed signals RPM[i](i=1,2...n) of the current effective speed sensors of the traction motor, wherein n is the number of axles of the locomotive, calculating an average speed value RPMav of the traction motor, a maximum speed value RPMmax of the traction motor, and a minimum speed value RPMmin of the traction motor in the whole locomotive, calculating an average speed value RPMTav of the traction motor, a maximum speed value RPMTmax of the traction motor, and a minimum speed value RPMTmin of the traction motor in each bogie, calculating a body-to-ground conversion speed estimated value RPMg.

5. The method of claim 4, characterized in that, the body-to-ground conversion speed estimated value RPMg is obtained by a radar speed measuring device or a non-power axle speed measuring device.

6. The method of claim 1, characterized in that, the adhesion control feedback factors is obtained according to the following formula: Adivl=31*AdF1, Adiv2=52*AdF2, Adiv3=383*AdF3, wherein, 81, 82, and 33 are weighting coefficients greater than 1 and less than 5, AdF1 is a transient acceleration / deceleration feedback parameter, AdF2 is a speed difference feedback parameter, and AdF3 is a acceleration limit feedback parameter.

7. The method of claim 1, characterized in that, in step 4, the transfer function adopted by the weighted adhesion control PI closed-loop controller TqAd is TqAdout = TqAdout + Kp[e(k)-e(k-1)]+Ki*e(k), wherein, Kp and Ki are a proportional parameter and an integral parameters of the PI closed-loop controller TqAd, e(k) is a difference between TqAdref and TqAdfdb at this time, e(k-1) is a difference between the TqAdref and TqAdfdb at the previous time.

8. The method of claim 1, characterized in that, in step 4, when the difference between the weighted adhesion control feedback value TqAdfdb and the weighted adhesion control reference value TqAdref is greater than P*TqAdref, the control system performs a sanding instruction of the corresponding axle position, wherin, 0.5<p<1.

9. The method of claim 6, characterized in that, the AdF1, AdF2 and AdF3 are calculated in the manner of locomotive control, bogie control and axle control.

10. A locomotive, characterized in that, adopting the weighted parameter adhesion control method of any one of claims 1-9.

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