CN114722343A - Clutch position signal filtering method and device, storage medium and terminal - Google Patents

Clutch position signal filtering method and device, storage medium and terminal Download PDF

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CN114722343A
CN114722343A CN202210227967.8A CN202210227967A CN114722343A CN 114722343 A CN114722343 A CN 114722343A CN 202210227967 A CN202210227967 A CN 202210227967A CN 114722343 A CN114722343 A CN 114722343A
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马金智
葛乃良
侯建军
左兰
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Weichai Power Co Ltd
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Abstract

The invention discloses a method and a device for filtering a clutch position signal, a storage medium and a terminal, wherein the method comprises the following steps: when a clutch position signal value at the current moment is obtained, determining a first prior estimation value corresponding to the previous moment at the current moment; performing Kalman filtering according to the first priori estimation value and the clutch position signal value at the current moment to generate a Kalman filtering result corresponding to the current moment; and judging whether secondary filtering is performed or not according to the Kalman filtering result, and determining a final filtering result based on the judged result. According to the method and the device, primary filtering is carried out on the clutch position signal by Kalman filtering, then secondary filtering is carried out on the signal by secondary filtering to further filter abnormal points, and meanwhile, the Kalman filtering parameter setting difficulty is reduced, so that optimization of control parameters is realized, and the frequency stability of the clutch position signal is improved.

Description

Clutch position signal filtering method and device, storage medium and terminal
Technical Field
The invention relates to the technical field of variable speed control, in particular to a method and a device for filtering a clutch position signal, a storage medium and a terminal.
Background
The position signal of the clutch is very critical, and if the position signal of the clutch is transmitted inaccurately, the torque transmission is easy to be unreasonable, so that the vehicle rushes to engage the gear when starting and has poor NVH (noise vibration harshness); meanwhile, the clutch still transmits torque when the gear is engaged, and gear beating occurs; the slipping and friction stage of the clutch can be identified as the complete combination stage by mistake, and the clutch is easy to burn; thereby causing gear-off, gear-on and gear-off failure. It is important to improve the accuracy of the clutch position signal.
In the prior art solution, the prior art applies low-pass filtering or PTI filtering to filter the clutch position, where the low-pass filtering expression is: y isn＝T*Xn+(1-T)*Yn-1(ii) a Where T is a time constant, dependent on the filter time constant and the sampling period, XnFor the filtered input of the nth sample, YnIs the filtered output of the nth sample. The PTI filtering expression is: y ═ y(x-1)+(x-y(x-1)) DT/TI; where x is the input signal before filtering, DT is the time interval, TI is the delay time constant, and y is the filtered output signal. Due to the low-pass filtering and the PTI filtering, there is a certain error in the accuracy of the signal, resulting in a slow signal responsiveness.
Disclosure of Invention
The embodiment of the application provides a method and a device for filtering a clutch position signal, a storage medium and a terminal. The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview and is intended to neither identify key/critical elements nor delineate the scope of such embodiments. Its sole purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is presented later.
In a first aspect, an embodiment of the present application provides a method for filtering a clutch position signal, where the method includes:
when a clutch position signal value at the current moment is obtained, determining a first prior estimation value corresponding to the previous moment at the current moment;
performing Kalman filtering according to the first priori estimation value and the clutch position signal value at the current moment to generate a Kalman filtering result corresponding to the current moment;
and judging whether secondary filtering is performed or not according to the Kalman filtering result, and determining a final filtering result based on the judged result.
Optionally, when the clutch position signal value at the current time is obtained, before determining the first prior estimate value corresponding to the previous time at the current time, the method further includes:
reconstructing a Kalman equation, and generating a state estimation and correction estimation equation of the clutch position;
acquiring an equation initialization parameter at an initial moment;
and calculating the prior estimation value of Kalman filtering at the initial moment according to the equation initialization parameter and the state estimation and correction estimation equation.
Optionally, when the clutch position signal value at the current time is obtained, determining a first prior estimate value corresponding to a time before the current time includes:
acquiring a clutch position signal value at the current moment;
and when the current moment is the next moment of the initial moment, determining the prior estimation value of the Kalman filtering at the initial moment as a first prior estimation value corresponding to the previous moment of the current moment.
Optionally, the kalman filtering includes a prediction process and an update process;
performing Kalman filtering according to the first priori estimation value and the clutch position signal value at the current moment to generate a Kalman filtering result corresponding to the current moment, wherein the Kalman filtering result comprises the following steps:
predicting a state value of the current moment according to the first prior estimation value;
updating the state value according to the clutch position signal value at the current moment to generate a second prior estimation value;
and generating a Kalman filtering result corresponding to the current moment according to the second prior estimation value.
Optionally, generating a kalman filtering result corresponding to the current time according to the second prior estimated value includes:
when the second prior estimation value is in a preset state value interval, determining the second prior estimation value as a Kalman filtering result corresponding to the current moment;
or,
and when the second prior estimation value is not in the preset state value interval, adjusting equation parameters of the state estimation and correction estimation equation, and continuously executing the step of determining the first prior estimation value corresponding to the previous moment of the current moment when the clutch position signal value of the current moment is obtained.
Optionally, determining whether to perform secondary filtering according to a kalman filtering result, including:
obtaining a final filtering result of the last moment corresponding to the current moment;
calculating a target difference value between a Kalman filtering result and a final filtering result at the last moment;
calculating the absolute value of the target difference;
when the absolute value is greater than or equal to a preset threshold value, determining that secondary filtering is required;
or,
and when the absolute value is smaller than a preset threshold value, determining that secondary filtering is not needed.
Optionally, determining a final filtering result based on the determined result includes:
when secondary filtering is not needed, determining a Kalman filtering result as a final filtering result;
or,
when secondary filtering is needed, counting the signals of which the absolute values are greater than or equal to a preset threshold value to generate a count value;
determining a final filtering result according to the count value, including:
when the count value is smaller than the preset count value, determining the final filtering result at the last moment as the final filtering result;
or,
and when the count value is greater than or equal to the preset count value, determining the Kalman filtering result at the last moment corresponding to the current moment as a final filtering result.
In a second aspect, an embodiment of the present application provides a clutch position signal filtering apparatus, including:
the prior estimation value determining module is used for determining a first prior estimation value corresponding to the previous moment of the current moment when the clutch position signal value of the current moment is obtained;
the Kalman filtering result generation module is used for carrying out Kalman filtering according to the first prior estimation value and the clutch position signal value at the current moment to generate a Kalman filtering result corresponding to the current moment;
and the final filtering result determining module is used for judging whether secondary filtering is performed according to the Kalman filtering result and determining the final filtering result based on the judged result.
In a third aspect, embodiments of the present application provide a computer storage medium having stored thereon a plurality of instructions adapted to be loaded by a processor and to perform the above-mentioned method steps.
In a fourth aspect, an embodiment of the present application provides a terminal, which may include: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the above-mentioned method steps.
The technical scheme provided by the embodiment of the application can have the following beneficial effects:
in the embodiment of the application, the clutch position signal filtering device firstly determines a first priori estimated value corresponding to the previous moment of the current moment when the clutch position signal value of the current moment is obtained, then performs Kalman filtering according to the first priori estimated value and the clutch position signal value of the current moment to generate a Kalman filtering result corresponding to the current moment, finally judges whether to perform secondary filtering according to the Kalman filtering result, and determines a final filtering result based on the judged result. According to the method and the device, primary filtering is carried out on the clutch position signal by Kalman filtering, then secondary filtering is carried out on the signal by secondary filtering to further filter abnormal points, and meanwhile, the Kalman filtering parameter setting difficulty is reduced, so that optimization of control parameters is realized, and the frequency stability of the clutch position signal is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
FIG. 1 is a schematic flow chart diagram illustrating a method for filtering a clutch position signal according to an embodiment of the present disclosure;
fig. 2 is a schematic flowchart of kalman filtering provided in an embodiment of the present application;
fig. 3 is a schematic block diagram of a process of filtering kalman filtering again according to an embodiment of the present disclosure;
FIG. 4 is a schematic structural diagram of a clutch position signal filtering apparatus according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a terminal according to an embodiment of the present application.
Detailed Description
The following description and the drawings sufficiently illustrate specific embodiments of the invention to enable those skilled in the art to practice them.
It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The following description refers to the accompanying drawings in which the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.
In the description of the present invention, it is to be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art. In addition, in the description of the present invention, "a plurality" means two or more unless otherwise specified. "and/or" describes the association relationship of the associated object, indicating that there may be three relationships, for example, a and/or B, which may indicate: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship.
The application provides a method and a device for filtering a clutch position signal, a storage medium and a terminal, which are used for solving the problems in the related art. In the technical scheme provided by the application, because the application utilizes Kalman filtering to carry out primary filtering on the clutch position signal, and then secondary filtering is carried out on the signal through secondary filtering to further filter abnormal points, and simultaneously, the Kalman filtering parameter setting difficulty is reduced, so that the optimization of control parameters is realized, the frequency stability of the clutch position signal is improved, and the detailed description is carried out by adopting an exemplary embodiment.
The following describes the filtering method of the clutch position signal according to the embodiment of the present application in detail with reference to fig. 1 to 3. The method may be implemented in dependence on a computer program, operable on a clutch position signal filtering device based on the von neumann architecture. The computer program may be integrated into the application or may run as a separate tool-like application.
Referring to fig. 1, a flow chart of a method for filtering a clutch position signal is provided according to an embodiment of the present application. As shown in fig. 1, the method of the embodiment of the present application may include the following steps:
s101, when a clutch position signal value at the current moment is obtained, determining a first prior estimation value corresponding to the previous moment at the current moment;
wherein, the filtering is the operation of filtering out the specific wave band frequency in the clutch position signal. The clutch position signal value is a signal obtained by a clutch position sensor.
Generally, the application provides a clutch position filtering algorithm applicable to a heavy truck TCU (transmission control unit), so that the clutch position precision is ensured, the optimization of control parameters is realized, the frequency stability of a clutch position signal is improved, and the gear shifting efficiency and accuracy are optimized.
In the embodiment of the application, before step S101, a priori estimated value of kalman filtering at an initial time needs to be calculated, a kalman equation is reconstructed first, a state estimation and revised estimation equation of the clutch position is generated, then an equation initialization parameter at the initial time is obtained, and finally the priori estimated value of kalman filtering at the initial time is calculated according to the equation initialization parameter and the state estimation and revised estimation equation.
In a possible implementation manner, a clutch position signal value at the current moment is obtained firstly, and then when the current moment is the next moment of the initial moment, the prior estimation value of the initial moment Kalman filtering is determined as the first prior estimation value corresponding to the previous moment of the current moment.
S102, performing Kalman filtering according to the first prior estimation value and the clutch position signal value at the current moment to generate a Kalman filtering result corresponding to the current moment;
specifically, the kalman filtering predicts the state value of the current time by using the optimal result of the previous time, and corrects the predicted value of the current state by using the observation value to obtain the optimal state estimation value of the current time.
Generally, kalman filtering is divided into two processes, namely prediction and update, and let time t be the current time and time t-1 be the last time.
And in the prediction process, the state value at the time t is predicted by using the optimal result at the time t-1 to obtain a priori estimation value. The expression is as follows:
Figure BDA0003536966530000061
wherein,
Figure BDA0003536966530000062
and
Figure BDA0003536966530000063
respectively representing a priori estimated value, an optimal state estimated value at t-1 moment, ut-1Indicating the control quantity of the system at time t-1, F, B indicating the state transition matrix and the control matrix respectively,
Figure BDA0003536966530000064
to represent
Figure BDA0003536966530000065
Q is the system process covariance.
And in the updating process, measuring the state value at the time t by using measuring instruments such as a sensor and the like, and correcting the prior estimated value to obtain the optimal state estimated value at the time t. The expression is as follows:
Figure BDA0003536966530000066
wherein k istFor Kalman gain, H is the measurement system matrix, R is the covariance of the measurement noise,
Figure BDA0003536966530000067
for an optimum state estimate at time t, ZtMeasured for time t, PtIs the error covariance.
In the embodiment of the application, if the previous moment of the current moment is an initial moment, when kalman filtering is performed, firstly, a state value of the current moment is predicted according to a first prior estimation value, then, the state value is updated according to a clutch position signal value of the current moment to generate a second prior estimation value, and finally, a kalman filtering result corresponding to the current moment is generated according to the second prior estimation value.
Specifically, when a kalman filtering result corresponding to the current time is generated according to the second prior estimation value, firstly, when the second prior estimation value is within a preset state value interval, the second prior estimation value is determined as the kalman filtering result corresponding to the current time; or when the second prior estimation value is not in the preset state value interval, adjusting equation parameters of the state estimation and correction estimation equation, and continuously executing the step of determining the first prior estimation value corresponding to the previous moment of the current moment when the clutch position signal value of the current moment is acquired.
In one possible implementation, such as shown in fig. 2, the kalman filtering result generating step is as follows: s1: and constructing a Kalman equation. Since the clutch position/motion model is not input and the position value at the next time is estimated only from the position value at the previous time, the state transition matrix F and the measurement system matrix H are set to 1, and the control quantity u is set to 1t-1And 0, obtaining a state estimation and correction estimation equation of the clutch position. S2: and initializing parameters. To pair
Figure BDA0003536966530000071
P0Q, R, carrying out initialization setting, and substituting the initialization setting into a state estimation and correction estimation equation of the clutch position to obtain a priori estimation value of the clutch position Kalman filtering at the initial moment. S3: and acquiring a clutch position signal value at the current moment through a clutch position sensor, and taking the clutch position signal value as a clutch position observed value. S4: and acquiring a clutch position signal value at the current moment through a clutch position sensor, and taking the clutch position signal value as a clutch position observed value. S5: and correcting the prior estimation value at the current moment through a Kalman filtering algorithm according to the prior estimation value and the observation value of Kalman filtering of the clutch position at the initial moment to obtain the optimal state estimation value of the clutch position at the current moment, and taking the optimal state estimation value as the prior estimation value of the clutch position at the next moment. Through the circulation of S3, S4 and S5, the clutch position signal completes the prediction and update processes, abnormal points are filtered, in the process, the hyper-parameter Q, R needs to be adjusted through manual setting, and a Kalman-filtered clutch position signal under an ideal condition, namely a Kalman filtering result, is obtained.
S103, judging whether secondary filtering is carried out or not according to the Kalman filtering result, and determining a final filtering result based on the judged result.
One difficulty of kalman filtering is setting and coordinating parameters, and the adjustment of Q, R should ensure that the abnormal point can be filtered out, and also should give consideration to the fast response of the initial value, which are difficult to coordinate. Therefore, secondary filtering is performed on the basis of Kalman filtering, the purpose is to further filter the abnormal point on the premise of ensuring quick response of the initial value, at the moment, the Kalman filtering Q, R is adjusted only by mainly considering the problem of quick response of the initial value, the filtering control of the abnormal point is within a certain range, and the abnormal point is reasonably filtered by the secondary filtering.
In the embodiment of the application, when whether secondary filtering is performed or not is judged according to the kalman filtering result, a final filtering result at the previous moment corresponding to the current moment is firstly obtained, then a target difference between the kalman filtering result and the final filtering result at the previous moment is calculated, an absolute value of the target difference is calculated, and finally when the absolute value is greater than or equal to a preset threshold, it is determined that secondary filtering is required. Or, when the absolute value is smaller than a preset threshold, it is determined that the secondary filtering is not required.
Specifically, when determining a final filtering result based on the result after the judgment, first, when the secondary filtering is not needed, determining a kalman filtering result as the final filtering result; or when secondary filtering is needed, counting the signals of which the absolute values are greater than or equal to a preset threshold value to generate a count value, and then determining a final filtering result according to the count value.
Specifically, when the final filtering result is determined according to the count value, firstly, when the count value is smaller than a preset count value, the final filtering result at the previous moment is determined as the final filtering result; or when the count value is greater than or equal to the preset count value, determining the Kalman filtering result at the last moment corresponding to the current moment as the final filtering result.
As shown in fig. 3, the two-stage filtering algorithm includes the following steps: and S6, judging that the value A of the Kalman filtering result is not less than or equal to a threshold value, wherein the value A is a final filtering result corresponding to the last time value of the current time, judging the absolute value of the difference between the Kalman filtering result and the value A through the threshold value, and the threshold value is not fixed and can be set according to the actual situation. If yes, the value is an abnormal point, and S7 is entered for counting; if not, the value is not an outlier, a deviation within a threshold range may be accepted, and the final filtering result is a kalman filtering result. And S7, counting the signal of which the value A | is more than or equal to the threshold value of the | Kalman filtering result, and playing the role of a counter. S8, the count value is judged to be < the set value, and the set value is not fixed and can be set according to the actual setting. If so, the final filtering result is the final filtering result at the last moment, and the error accumulation is considered to be in a reasonable range when the error accumulation exists; if not, the accumulated error exceeds a reasonable range, the final filtering result needs to be corrected, and the final filtering result is the Kalman filtering result at the last moment.
It should be noted that, kalman filtering is used for filtering the clutch position signal for the first time, so that the signal delay is small, and the precision of the clutch position signal can be effectively improved; a counter function is added in the secondary filtering, and the counting value can be calibrated, so that the recording of an abnormal point is realized, and the filtering effect is improved; the Kalman filtering result is fed back to the secondary filtering, so that the Kalman filtering parameter setting difficulty can be effectively reduced, and the initial value quick response and the filtering result optimization are realized.
Further, the clutch position filtering algorithm of the heavy truck TCU of the present application is applicable to, but not limited to, clutch position signals.
In the embodiment of the application, when the clutch position signal value at the current moment is obtained, the clutch position signal filtering device firstly determines a first prior estimation value corresponding to the previous moment at the current moment, then performs kalman filtering according to the first prior estimation value and the clutch position signal value at the current moment to generate a kalman filtering result corresponding to the current moment, finally judges whether to perform secondary filtering according to the kalman filtering result, and determines a final filtering result based on the judged result. According to the method and the device, primary filtering is carried out on the clutch position signal by Kalman filtering, then secondary filtering is carried out on the signal by secondary filtering to further filter abnormal points, and meanwhile, the Kalman filtering parameter setting difficulty is reduced, so that optimization of control parameters is realized, and the frequency stability of the clutch position signal is improved.
The following are embodiments of the apparatus of the present invention that may be used to perform embodiments of the method of the present invention. For details which are not disclosed in the embodiments of the apparatus of the present invention, reference is made to the embodiments of the method of the present invention.
Referring to fig. 4, a schematic structural diagram of a clutch position signal filtering device according to an exemplary embodiment of the present invention is shown. The clutch position signal filtering means may be implemented as all or part of the terminal by software, hardware or a combination of both. The device 1 comprises an a priori estimation value determining module 10, a Kalman filtering result generating module 20 and a final filtering result determining module 30.
The prior estimation value determining module 10 is configured to determine a first prior estimation value corresponding to a previous time of a current time when a clutch position signal value of the current time is obtained;
the kalman filtering result generating module 20 is configured to perform kalman filtering according to the first apriori estimated value and the clutch position signal value at the current time, and generate a kalman filtering result corresponding to the current time;
and a final filtering result determining module 30, configured to determine whether to perform secondary filtering according to the kalman filtering result, and determine a final filtering result based on the determined result.
It should be noted that, when the clutch position signal filtering apparatus provided in the foregoing embodiment executes the clutch position signal filtering method, only the division of the above functional modules is taken as an example, and in practical applications, the above functions may be distributed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules, so as to complete all or part of the functions described above. In addition, the clutch position signal filtering device provided by the above embodiment and the clutch position signal filtering method embodiment belong to the same concept, and the details of the implementation process are referred to the method embodiment, which are not described herein again.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
In the embodiment of the application, when the clutch position signal value at the current moment is obtained, the clutch position signal filtering device firstly determines a first prior estimation value corresponding to the previous moment at the current moment, then performs kalman filtering according to the first prior estimation value and the clutch position signal value at the current moment to generate a kalman filtering result corresponding to the current moment, finally judges whether to perform secondary filtering according to the kalman filtering result, and determines a final filtering result based on the judged result. According to the method and the device, primary filtering is carried out on the clutch position signal by Kalman filtering, then secondary filtering is carried out on the signal by secondary filtering to further filter abnormal points, and meanwhile, the Kalman filtering parameter setting difficulty is reduced, so that optimization of control parameters is realized, and the frequency stability of the clutch position signal is improved.
The present invention also provides a computer readable medium having stored thereon program instructions that, when executed by a processor, implement the clutch position signal filtering method provided by the various method embodiments described above. The present invention also provides a computer program product containing instructions which, when run on a computer, cause the computer to perform the method of filtering a clutch position signal of the various method embodiments described above.
Please refer to fig. 5, which provides a schematic structural diagram of a terminal according to an embodiment of the present application. As shown in fig. 5, terminal 1000 can include: at least one processor 1001, at least one network interface 1004, a user interface 1003, memory 1005, at least one communication bus 1002.
Wherein a communication bus 1002 is used to enable connective communication between these components.
The user interface 1003 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 1003 may also include a standard wired interface and a wireless interface.
The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.
Processor 1001 may include one or more processing cores, among other things. The processor 1001, which is connected to various parts throughout the electronic device 1000 using various interfaces and lines, performs various functions of the electronic device 1000 and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 1005 and calling data stored in the memory 1005. Alternatively, the processor 1001 may be implemented in at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor 1001 may integrate one or more of a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), a modem, and the like. Wherein, the CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It is understood that the modem may not be integrated into the processor 1001, but may be implemented by a single chip.
The Memory 1005 may include a Random Access Memory (RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 1005 includes a non-transitory computer-readable medium. The memory 1005 may be used to store an instruction, a program, code, a set of codes, or a set of instructions. The memory 1005 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the various method embodiments described above, and the like; the storage data area may store data and the like referred to in the above respective method embodiments. The memory 1005 may optionally be at least one memory device located remotely from the processor 1001. As shown in fig. 5, the memory 1005, which is one type of computer storage medium, may include an operating system, a network communication module, a user interface module, and a clutch position signal filtering application.
In the terminal 1000 shown in fig. 5, the user interface 1003 is mainly used as an interface for providing input for a user, and acquiring data input by the user; and the processor 1001 may be configured to invoke the clutch position signal filtering application stored in the memory 1005 and specifically perform the following operations:
when a clutch position signal value at the current moment is obtained, determining a first prior estimation value corresponding to the previous moment at the current moment;
performing Kalman filtering according to the first prior estimation value and the clutch position signal value at the current moment to generate a Kalman filtering result corresponding to the current moment;
and judging whether secondary filtering is performed or not according to the Kalman filtering result, and determining a final filtering result based on the judged result.
In one embodiment, the processor 1001, when executing the determining before the first a priori estimate value corresponding to the time previous to the current time when the clutch position signal value at the current time is acquired, further executes the following operations:
reconstructing a Kalman equation, and generating a state estimation and correction estimation equation of the clutch position;
acquiring an equation initialization parameter at an initial moment;
and calculating the prior estimation value of Kalman filtering at the initial moment according to the equation initialization parameter and the state estimation and correction estimation equation.
In one embodiment, when determining the first a priori estimated value corresponding to the time before the current time when obtaining the clutch position signal value at the current time, the processor 1001 specifically performs the following operations:
acquiring a clutch position signal value at the current moment;
and when the current moment is the next moment of the initial moment, determining the prior estimation value of the initial moment Kalman filtering as a first prior estimation value corresponding to the previous moment of the current moment.
In one embodiment, when performing kalman filtering according to the first a-priori estimate value and the clutch position signal value at the current time to generate a kalman filtering result corresponding to the current time, the processor 1001 specifically performs the following operations:
predicting a state value of the current moment according to the first prior estimation value;
updating the state value according to the clutch position signal value at the current moment to generate a second prior estimation value;
and generating a Kalman filtering result corresponding to the current moment according to the second prior estimation value.
In an embodiment, when the processor 1001 performs the kalman filtering result corresponding to the current time according to the second a priori estimated value, specifically performs the following operations:
when the second prior estimation value is in a preset state value interval, determining the second prior estimation value as a Kalman filtering result corresponding to the current moment;
or,
and when the second prior estimation value is not in the preset state value interval, adjusting equation parameters of the state estimation and correction estimation equation, and continuously executing the step of determining the first prior estimation value corresponding to the previous moment of the current moment when the clutch position signal value of the current moment is obtained.
In one embodiment, when the processor 1001 determines whether to perform the second filtering according to the kalman filtering result, the following operations are specifically performed:
obtaining a final filtering result of the last moment corresponding to the current moment;
calculating a target difference value between a Kalman filtering result and a final filtering result at the last moment;
calculating the absolute value of the target difference;
when the absolute value is greater than or equal to a preset threshold value, determining that secondary filtering is required;
or,
and when the absolute value is smaller than a preset threshold value, determining that secondary filtering is not needed.
In one embodiment, the processor 1001 specifically performs the following operations when determining the final filtering result based on the determined result:
when secondary filtering is not needed, determining a Kalman filtering result as a final filtering result;
or,
when secondary filtering is needed, counting the signals of which the absolute values are greater than or equal to a preset threshold value to generate a count value;
determining a final filtering result according to the count value, including:
when the count value is smaller than the preset count value, determining the final filtering result at the last moment as the final filtering result;
or,
and when the count value is greater than or equal to the preset count value, determining the Kalman filtering result at the last moment corresponding to the current moment as a final filtering result.
In the embodiment of the application, when the clutch position signal value at the current moment is obtained, the clutch position signal filtering device firstly determines a first prior estimation value corresponding to the previous moment at the current moment, then performs kalman filtering according to the first prior estimation value and the clutch position signal value at the current moment to generate a kalman filtering result corresponding to the current moment, finally judges whether to perform secondary filtering according to the kalman filtering result, and determines a final filtering result based on the judged result. According to the method and the device, primary filtering is carried out on the clutch position signal by Kalman filtering, then secondary filtering is carried out on the signal by secondary filtering to further filter abnormal points, and meanwhile, the Kalman filtering parameter setting difficulty is reduced, so that optimization of control parameters is realized, and the frequency stability of the clutch position signal is improved.
It will be understood by those skilled in the art that all or part of the processes of the methods of the above embodiments may be implemented by a computer program to instruct associated hardware, and that the program for filtering the clutch position signal may be stored in a computer readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a read-only memory or a random access memory.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present application and should not be taken as limiting the scope of the present application, so that the present application will be covered by the appended claims.

Claims (10)

1. A method of filtering a clutch position signal, the method comprising:
when a clutch position signal value at the current moment is obtained, determining a first prior estimation value corresponding to the previous moment of the current moment;
performing Kalman filtering according to the first prior estimation value and the clutch position signal value at the current moment to generate a Kalman filtering result corresponding to the current moment;
and judging whether secondary filtering is performed or not according to the Kalman filtering result, and determining a final filtering result based on the judged result.
2. The method of claim 1, wherein determining the value of the clutch position signal at the current time before determining the first a priori estimate corresponding to the time immediately preceding the current time when the value of the clutch position signal at the current time is obtained further comprises:
reconstructing a Kalman equation, and generating a state estimation and correction estimation equation of the clutch position;
acquiring an equation initialization parameter at an initial moment;
and calculating a priori estimation value of Kalman filtering at the initial moment according to the equation initialization parameter and the state estimation and correction estimation equation.
3. The method of claim 2, wherein determining a first a priori estimate corresponding to a time previous to a current time when a clutch position signal value at the current time is obtained comprises:
acquiring a clutch position signal value at the current moment;
and when the current moment is the next moment of the initial moment, determining the prior estimation value of the initial moment Kalman filtering as a first prior estimation value corresponding to the previous moment of the current moment.
4. The method of claim 2, wherein the kalman filtering comprises a prediction process and an update process;
and performing Kalman filtering according to the first prior estimation value and the clutch position signal value at the current moment to generate a Kalman filtering result corresponding to the current moment, wherein the Kalman filtering result comprises the following steps:
predicting a state value at the current moment according to the first prior estimation value;
updating the state value according to the clutch position signal value at the current moment to generate a second prior estimation value;
and generating a Kalman filtering result corresponding to the current moment according to the second prior estimation value.
5. The method according to claim 4, wherein generating a kalman filtering result corresponding to the current time according to the second a priori estimated value comprises:
when the second prior estimation value is in a preset state value interval, determining the second prior estimation value as a Kalman filtering result corresponding to the current moment;
or,
and when the second prior estimation value is not in a preset state value interval, adjusting equation parameters of the state estimation and correction estimation equation, and continuously executing the step of determining the first prior estimation value corresponding to the previous moment of the current moment when the clutch position signal value of the current moment is obtained.
6. The method according to claim 1, wherein the determining whether to perform secondary filtering according to the kalman filtering result comprises:
obtaining a final filtering result of the last moment corresponding to the current moment;
calculating a target difference value between the Kalman filtering result and a final filtering result at the last moment;
calculating an absolute value of the target difference;
when the absolute value is greater than or equal to a preset threshold value, determining that secondary filtering is required;
or,
and when the absolute value is smaller than a preset threshold value, determining that secondary filtering is not required.
7. The method of claim 6, wherein determining a final filtering result based on the determined result comprises:
when secondary filtering is not needed, determining the Kalman filtering result as a final filtering result;
or,
when secondary filtering is needed, counting the signals of which the absolute values are greater than or equal to a preset threshold value to generate a count value;
determining a final filtering result according to the count value, including:
when the count value is smaller than a preset count value, determining the final filtering result at the last moment as a final filtering result;
or,
and when the count value is greater than or equal to a preset count value, determining the Kalman filtering result at the last moment corresponding to the current moment as a final filtering result.
8. A clutch position signal filtering device, the device comprising:
the device comprises a priori estimation value determining module, a priori estimation value determining module and a clutch position signal value determining module, wherein the priori estimation value determining module is used for determining a first priori estimation value corresponding to the previous moment of the current moment when the clutch position signal value of the current moment is obtained;
the Kalman filtering result generation module is used for carrying out Kalman filtering according to the first prior estimation value and the clutch position signal value at the current moment to generate a Kalman filtering result corresponding to the current moment;
and the final filtering result determining module is used for judging whether secondary filtering is performed according to the Kalman filtering result and determining a final filtering result based on the judged result.
9. A computer storage medium, characterized in that it stores a plurality of instructions adapted to be loaded by a processor and to perform the method steps according to any one of claims 1 to 7.
10. A terminal, comprising: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and to perform the method steps of any of claims 1-7.
CN202210227967.8A 2022-03-08 2022-03-08 Clutch position signal filtering method and device, storage medium and terminal Pending CN114722343A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115460047A (en) * 2022-08-02 2022-12-09 北京睿信丰科技有限公司 Method and device for quickly tracking frequency deviation and distance under complex channel and electronic equipment

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115460047A (en) * 2022-08-02 2022-12-09 北京睿信丰科技有限公司 Method and device for quickly tracking frequency deviation and distance under complex channel and electronic equipment
CN115460047B (en) * 2022-08-02 2024-06-11 北京睿信丰科技有限公司 Method and device for quickly tracking frequency offset and distance under complex channel and electronic equipment

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