Complex signal multi-drive intelligent identification motor rotating speed control method and system

Abstract

The invention belongs to the technical field of signal identification, and particularly relates to a complex signal multi-drive intelligent identification motor rotating speed control method and system, and the method comprises the steps: obtaining an automobile fan signal; performing signal validity identification based on the automobile fan signal to obtain an effective signal, and identifying and determining a signal type; calling a rotating speed function corresponding to the signal type based on the identified signal type, and obtaining a fan simulation rotating speed corresponding to the signal type; environment temperature and automobile fan internal temperature are collected in real time, an environment temperature collection speed compensation model and a fan temperature collection speed compensation model are constructed in a fitting mode, and the fan simulation rotating speed corresponding to the signal type is combined to determine the fan theoretical rotating speed corresponding to the signal type; and comparing the real-time rotating speed of the fan with the theoretical rotating speed of the fan to obtain a comparison result, and compensating the real-time rotating speed of the fan to the theoretical rotating speed of the fan by utilizing a fan dynamic balance model in combination with the current and magnetic field intensity of the fan, so that the reversing angle of the automobile fan is adjusted, and the optimal running state is achieved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of signal recognition, and particularly relates to a complex signal multi-drive intelligent recognition motor speed control method and system. BACKGROUND

[0002] In the field of automotive electronic control, the automobile fan as a key thermal management component, its stable operation depends on the accurate identification and processing of multiple complex control signals. These signal types cover analog signals, digital signals and LIN bus signals, each signal has unique level characteristics, timing characteristics and data coding methods. In the automobile electrical system, the electromagnetic interference problem caused by the dense deployment of electronic equipment is particularly prominent, the signal is easily polluted by noise in the transmission process, causing signal distortion or misjudgment, and then affecting the accuracy and reliability of the fan speed control.

[0003] The traditional fan control system mostly adopts a single signal recognition mechanism, lacks dynamic adaptation ability to multi-mode signals, and does not fully consider the influence of electromagnetic interference on signal integrity. In terms of temperature compensation, the existing technology usually only makes simple correction based on the environment temperature or the motor body temperature, and fails to establish a dynamic compensation model coupled with multiple physical fields, resulting in unstable output performance of the motor under complex working conditions (such as temperature sudden change, magnetic field fluctuation). In addition, the motor commutation control mostly relies on fixed angle parameters, and does not dynamically adjust according to the real-time running state (such as current fluctuation, magnetic field strength change), which limits the improvement of motor efficiency and service life. SUMMARY

[0004] The application provides a complex signal multi-drive intelligent recognition motor speed control method and system, which effectively identifies and identifies the signals of the automobile fan, introduces a temperature compensation mechanism to determine the theoretical speed of the fan, and adjusts the speed of the automobile fan in combination with the real-time speed of the fan. The automobile fan speed compensation adjustment is realized, the automobile fan speed accurate control is realized, the automobile fan commutation angle is adjusted, the closed-loop control from multi-modal signal recognition to multi-parameter real-time compensation is realized, and the automobile fan is always ensured to be in the best operating state. The stability and efficiency of the automobile fan running in a complex signal environment are improved.

[0005] A complex signal multi-drive intelligent recognition motor speed control method, comprising: Obtaining automobile fan signals; Based on the automobile fan signals, signal effectiveness identification is performed to obtain effective signals; Based on the effective signals, signal type identification is performed to determine the signal type; Based on the identified signal type, a speed function corresponding to the signal type is called to obtain a fan analog speed corresponding to the signal type; Real-time acquisition of ambient temperature and internal temperature of automobile fan, fitting and constructing ambient temperature acquisition speed compensation model and fan temperature acquisition speed compensation model, and combining with the fan simulation speed corresponding to the signal type, determining the fan theoretical speed corresponding to the signal type; Comparing the real-time speed of the fan with the theoretical speed of the fan, obtaining the comparison result, and combining the fan current and magnetic field strength, using the fan dynamic balance model to compensate the real-time speed of the fan to the theoretical speed of the fan, so that the automobile fan adjusts the commutation angle and reaches the best operating state.

[0006] Through effective signal recognition and type recognition of automobile fan signals, and introducing a temperature compensation mechanism to determine the theoretical speed of the fan, and combining the real-time speed of the fan for targeted automobile fan speed compensation adjustment, accurate control of the speed of the automobile fan is realized, and the commutation angle of the automobile fan is adjusted, thereby realizing closed-loop control from multi-modal signal recognition to real-time compensation of multiple parameters, and always ensuring that the automobile fan is in the best operating state, and improving the stability and efficiency of the automobile fan in a complex signal environment.

[0007] Further, the signal effectiveness recognition based on the automobile fan signal includes: Based on the automobile fan signal, the fan signal peak value, fan signal start time and fan signal end time are obtained; The fan signal waveform area is calculated in combination with the fan signal peak value, fan signal start time and fan signal end time; The fan signal waveform area is compared with the effective area domain, and the fan signal falling into the effective area domain is taken as the effective signal.

[0008] By calculating the signal waveform area and comparing it with the effective area threshold, interference signals caused by environmental electromagnetic noise are filtered out, thereby reducing the probability of false operation from the source.

[0009] Further, the signal type recognition based on the effective signal includes: Based on the effective signal in a fixed time period, the minimum level and maximum level of the effective signal are obtained; When the minimum level is in the high level range and the maximum level is in the high level range, it is determined that the current signal is an analog signal; When the minimum level is in the low level range and the maximum level is in the high level range, and the variance of the continuous multiple high level duration is less than a preset threshold, it is determined that the current signal is a digital signal; When the minimum level is in the low level range and the maximum level is in the high level range, and the variance of the continuous multiple high level duration is not less than a preset threshold, it is determined that the current signal is a LIN signal.

[0010] By judging the level range of valid signals, the system can accurately distinguish and identify analog signals, digital signals, and LIN signals, solving the compatibility problem of multiple signals coexisting and improving the system's versatility and flexibility.

[0011] Furthermore, real-time ambient temperature and the internal temperature of the vehicle's fan are collected. An ambient temperature acquisition speed compensation model and a fan temperature acquisition speed compensation model are then fitted and constructed. Combined with the simulated fan speed corresponding to the signal type, the theoretical fan speed corresponding to the signal type is determined, including: Multiple ambient temperatures are continuously collected within a fixed time period. An ambient temperature fitting function is constructed, and an ambient temperature acquisition speed compensation model is built based on the ambient temperature fitting function to determine the ambient temperature acquisition speed compensation coefficient. The internal temperature of multiple automotive fans was continuously collected within a fixed time period. A fan temperature fitting function was constructed, and based on the fan temperature fitting function, a fan temperature acquisition speed compensation model was constructed to determine the ambient temperature acquisition speed compensation coefficient. Based on the ambient temperature acquisition speed compensation coefficient and the simulated fan speed corresponding to the signal type, the theoretical fan speed corresponding to the signal type is determined.

[0012] By continuously sampling and fitting the temperature change trend, capturing the dynamic temperature change process, constructing a temperature acquisition speed compensation model, and then predicting the impact of temperature on the fan speed, soft compensation for the fan speed is achieved, avoiding the impact of temperature fluctuations.

[0013] Furthermore, the expression for the ambient temperature fitting function is: ; In the formula, Indicates the first An ambient temperature value, , This indicates the total number of ambient temperature samples collected. This represents the ambient temperature fitting function; Indicates the first Ambient temperature collection time; The expression for the environmental temperature acquisition rate compensation model is: ; In the formula, This represents the environmental temperature acquisition rate compensation coefficient. Indicates the ambient temperature compensation coefficient; This represents the compensation coefficient for the rate of change of ambient temperature. The expression for the fan temperature fitting function is: ; In the formula, represents the internal temperature value of the fan, , represents the total number of fan internal temperature collection; represents the fan internal temperature fitting function; represents the internal temperature value of the fan, The expression of the fan temperature collection speed compensation model is: ; In the formula, represents the fan temperature collection speed compensation coefficient; represents the fan internal temperature compensation coefficient; represents the fan internal temperature change rate compensation coefficient; The expression of the fan theoretical speed is: ; In the formula, represents the fan theoretical speed; represents the speed function corresponding to the analog signal; represents the speed function corresponding to the digital signal; represents the speed function corresponding to the LIN signal.

[0014] Further, the fan real-time speed and the fan theoretical speed are compared to obtain a comparison result, and the fan current and the magnetic field strength are combined to compensate the fan real-time speed to the fan theoretical speed by using the fan dynamic balance model, so that the automobile fan adjusts the commutation angle and reaches the best operating state, including: The fan real-time speed and the fan theoretical speed are compared to obtain a comparison result; The magnetic field strength is collected in real time, combined with the effective signal, a magnetic field strength compensation model is constructed, and a magnetic field strength compensation coefficient is determined; The fan dynamic balance model is constructed by combining the fan theoretical speed, the fan real-time speed, the fan reference current, the fan real-time current, and the magnetic field strength compensation coefficient; Based on the comparison result, the fan dynamic balance model is used to calculate and adjust the commutation angle of the automobile fan, so that the fan real-time speed is compensated to the fan theoretical speed, and the automobile fan reaches the best operating state.

[0015] By constructing the fan dynamic balance model, a multi-input closed-loop feedback system is obtained, so that the commutation angle of the automobile fan is dynamically adjusted according to the comparison result, the real-time calibration and adaptive optimization of the automobile fan speed are realized, and the automobile fan is always in the best operating state, achieving the dual effects of energy saving and consumption reduction and improving dynamic response.

[0016] ​​Further, the real-time acquisition of the magnetic field intensity, in combination with the effective signal, constructs a magnetic field intensity compensation model, and determines a magnetic field intensity compensation coefficient, comprising: Based on the effective signal, the waveform of the automobile fan and the back electromotive force waveform are acquired in real time, and the automobile fan actual frequency and the automobile fan back electromotive force waveform actual frequency are determined; The magnetic field actual intensity and the magnetic field reference intensity are acquired, in combination with the automobile fan back electromotive force waveform actual frequency, a magnetic field intensity compensation model is constructed, and a magnetic field intensity compensation coefficient is determined.

[0017] By constructing the magnetic field intensity compensation model, the influence of the magnetic field change can be corrected in real time, the stability of the output power and the speed control precision are guaranteed, and the service life of the automobile fan is prolonged.

[0018] Further, the expression of the magnetic field intensity compensation model is: ; In the formula, represents the magnetic field compensation coefficient; represents the automobile fan commutation frequency constant; represents the automobile fan back electromotive force waveform actual frequency; represents the automobile fan back electromotive force waveform actual frequency; represents the automobile fan actual frequency; represents the magnetic field intensity constant; represents the magnetic field actual intensity; represents the magnetic field reference intensity.

[0019] Further, the expression of the fan dynamic balance model is: ; In the formula, represents the commutation angle; represents the magnetic field intensity compensation constant; represents the fan reference current; represents the fan real-time current; represents the fan real-time speed; represents the actual commutation angle constant.

[0020] A system of a complex signal multiple drive intelligent recognition motor speed control method, comprising: A signal acquisition and recognition module acquires automobile fan signals; based on the automobile fan signals, signal effectiveness recognition is performed to obtain effective signals; based on the effective signals, signal type recognition is performed to determine the signal type; The rotation speed calculation module calls a rotation speed function corresponding to the identified signal type to obtain a fan simulation rotation speed corresponding to the signal type; the environmental temperature and the internal temperature of the automobile fan are collected in real time, and an environmental temperature collection speed compensation model and a fan temperature collection speed compensation model are fitted and constructed, and the fan simulation rotation speed corresponding to the signal type is combined to determine a fan theoretical rotation speed corresponding to the signal type; The discrimination and adjustment module compares the fan real-time rotation speed with the fan theoretical rotation speed to obtain a comparison result, and combines the fan current and the magnetic field strength to compensate the fan real-time rotation speed to the fan theoretical rotation speed by using a fan dynamic balance model, so that the automobile fan is adjusted in the commutation angle and reaches the best operating state.

[0021] The beneficial effects of the present application are: The present application realizes accurate control of the automobile fan rotation speed by performing effective recognition and type recognition of the automobile fan signal, introducing a temperature compensation mechanism to determine the fan theoretical rotation speed, and combining the fan real-time rotation speed to perform targeted automobile fan rotation speed compensation adjustment, and adjusts the commutation angle of the automobile fan, thereby realizing closed-loop control from multi-modal signal recognition to multi-parameter real-time compensation, and always ensuring that the automobile fan is in the best operating state, and improving the stability and efficiency of the automobile fan operation in a complex signal environment. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 The flowchart of the present application is shown in the figure; Figure 2 The system structure schematic diagram of the present application is shown in the figure. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0024] It should be noted that the various aspects of the embodiments described below are within the scope of the appended claims. It should be apparent that the aspects described herein can be embodied in a wide variety of forms, and that any specific structure and / or function described herein is merely illustrative. Based on the disclosure provided, one skilled in the art should appreciate that an aspect described herein can be implemented independently of any other aspects without departing from the scope of the present disclosure, and that two or more of these aspects can be combined in any suitable manner. For example, an apparatus can be implemented or a method can be practiced using any number of the aspects set forth herein. In addition, an apparatus can be implemented or a method can be practiced using other structure and / or functionality in addition to or other than one or more of the aspects set forth herein.

[0025] In addition, in the following description, specific details are provided for the purpose of thorough understanding of examples, and the above-mentioned terms can be understood in the specific meaning in the present application according to the specific circumstances for those skilled in the art.

[0026] Embodiment 1 Figure 1 A complex signal multi-drive intelligent recognition motor speed control method is shown, which realizes accurate control of the automobile fan speed by performing effective identification and type identification of the automobile fan signal, introducing a temperature compensation mechanism to determine the theoretical speed of the fan, and combining the real-time speed of the fan to perform targeted automobile fan speed compensation adjustment, adjusts the reversing angle of the automobile fan, and further realizes the closed-loop control from multi-modal signal recognition to multi-parameter real-time compensation, and always ensures that the automobile fan is in the best operating state, and improves the stability and efficiency of the automobile fan operation in a complex signal environment. Specifically includes the following steps: S1: obtaining an automobile fan signal; S2: based on the automobile fan signal, performing signal effectiveness identification to obtain an effective signal; S21: based on the automobile fan signal, obtaining a fan signal peak value, a fan signal start time , and a fan signal end time ; S22: combining the fan signal peak value, the fan signal start time , and the fan signal end time , calculating the fan signal waveform area; Wherein, the calculation expression of the fan signal waveform area is: ; In the formula, represents the fan signal waveform area; represents the fan signal waveform function; represents time; S23: comparing the fan signal waveform area with the effective area domain, and taking the fan signal falling into the effective area domain as an effective signal; In the present embodiment, the effective area domain is set as , that is, when , it is determined that the fan signal is effective.

[0027] S3: based on the effective signal, performing signal type identification to determine the signal type; S31: based on the effective signal in a fixed time period, obtaining the minimum level and the maximum level of the effective signal; S32: when the minimum level in the high level range, maximum level when in the high level range, determine that the current signal is an analog signal; S33: when the minimum level in the low level range, maximum level when in the high level range, and the variance of the continuous multiple high level durations is less than the preset threshold, determine that the current signal is a digital signal; S34: when the minimum level in the low level range, maximum level when in the high level range, and the variance of the continuous multiple high level durations is not less than the preset threshold, determine that the current signal is a LIN signal; In this embodiment, when the signal level is less than 1.5, it is determined that the signal level is low; when the signal level is not less than 1.5, it is determined that the signal level is high.

[0028] wherein the variance of the continuous multiple high level durations is obtained by continuously obtaining multiple high level times and calculating the time characteristics of the obtained multiple high level times. In this embodiment, 5 high level times 、 、 、 、 , the corresponding variance is calculated and compared with the set threshold to determine the signal type. The calculation expression of the variance of the continuous multiple high level durations is: ; wherein, represents the variance of the continuous multiple high level durations; represents the high level time, ; S4: based on the identified signal type, call the speed function corresponding to the signal type to obtain the fan analog speed corresponding to the signal type; S41: based on the analog signal, call the speed function of the analog signal to determine the fan analog speed of the analog signal; In this embodiment, the expression of the speed function of the analog signal is: ; wherein, represents the fan analog speed of the analog signal; represents the speed function of the analog signal, represents the analog signal voltage value; represents the function parameter corresponding to the analog signal; S42: Based on the digital signal, retrieve the speed function of the digital signal to determine the simulated fan speed of the digital signal; In this embodiment, the expression for the rotational speed function of the digital signal is: ; In the formula, The simulated rotational speed of the fan is represented by a digital signal; The rotational speed function representing the digital signal. Indicates the duty cycle of a digital signal; This represents the function parameters corresponding to the digital signal; S43: Based on the LIN signal, retrieve the speed function of the LIN signal to determine the simulated fan speed of the LIN signal; In this embodiment, the expression for the rotational speed function of the LIN signal is: ; In the formula, The LIN signal represents the simulated speed of the fan. The rotational speed function representing the LIN signal. Indicates LIN signal bytes; This represents the function parameters corresponding to the LIN signal; This represents the rotational speed constant corresponding to the LIN signal; S5: Real-time acquisition of ambient temperature and internal temperature of the car fan, fitting and constructing an ambient temperature acquisition speed compensation model and a fan temperature acquisition speed compensation model, and combining the simulated fan speed corresponding to the signal type to determine the theoretical fan speed corresponding to the signal type; S51: Continuously collect multiple ambient temperatures within a fixed time period, fit and construct an ambient temperature fitting function, and construct an ambient temperature acquisition speed compensation model based on the ambient temperature fitting function to determine the ambient temperature acquisition speed compensation coefficient. The expression for the ambient temperature fitting function is as follows: ; In the formula, Indicates the first An ambient temperature value, , This indicates the total number of ambient temperature samples collected. This represents the ambient temperature fitting function; Indicates the first Ambient temperature collection time; In this embodiment, six ambient temperatures are collected within 1 minute, i.e. .

[0029] The expression for the ambient temperature acquisition rate compensation model is as follows: ; wherein, represents the ambient temperature acquisition speed compensation coefficient; represents the ambient temperature compensation coefficient; represents the ambient temperature change rate compensation coefficient; S52: continuously acquire a plurality of automobile fan internal temperatures in a fixed time period, fit to construct a fan temperature fitting function, and based on the fan temperature fitting function, construct a fan temperature acquisition speed compensation model to determine the ambient temperature acquisition speed compensation coefficient; wherein, the expression of the fan temperature fitting function is: ; wherein, represents the first fan internal temperature value, , represents the total number of fan internal temperature acquisitions; represents the fan internal temperature fitting function; represents the first fan internal temperature acquisition time; In this embodiment, 6 automobile fan internal temperatures are acquired within 1 min, i.e. .

[0030] wherein, the expression of the fan temperature acquisition speed compensation model is: ; wherein, represents the fan temperature acquisition speed compensation coefficient; represents the fan internal temperature compensation coefficient; represents the fan internal temperature change rate compensation coefficient; S53: based on the ambient temperature acquisition speed compensation coefficient and the ambient temperature acquisition speed compensation coefficient, in combination with the fan simulated speed corresponding to the signal type, determine the fan theoretical speed corresponding to the signal type.

[0031] wherein, the expression of the fan theoretical speed is: ; wherein, represents the fan theoretical speed; represents the speed function corresponding to the analog signal; represents the speed function corresponding to the digital signal; represents the speed function corresponding to the LIN signal.

[0032] S6: Compare the real-time speed of the fan with the theoretical speed of the fan, obtain the comparison result, combine the fan current and the magnetic field strength, and use the fan dynamic balance model to compensate the real-time speed of the fan to the theoretical speed of the fan, so that the automobile fan adjusts the commutation angle and reaches the best operating state; S61: Compare the real-time speed of the fan with the theoretical speed of the fan, obtain the comparison result; S62: Real-time acquisition of magnetic field strength, combined with effective signal, construction of magnetic field strength compensation model, determination of magnetic field strength compensation coefficient; S621: Based on the effective signal, real-time acquisition of the waveform of the automobile fan and the back electromotive force waveform, determination of the actual frequency of the automobile fan and the actual frequency of the automobile fan back electromotive force waveform; S62: Obtain the actual strength of the magnetic field and the reference strength of the magnetic field, combine the actual frequency of the automobile fan back electromotive force waveform, construct the magnetic field strength compensation model, and determine the magnetic field strength compensation coefficient.

[0033] Wherein, the expression of the magnetic field strength compensation model is: ; In the formula, Indicates the magnetic field compensation coefficient; Indicates the commutation frequency constant of the automobile fan; Indicates the actual frequency of the automobile fan back electromotive force waveform; Indicates the actual frequency of the automobile fan back electromotive force waveform; Indicates the actual frequency of the automobile fan; Indicates the magnetic field strength constant; Indicates the actual strength of the magnetic field; Indicates the reference strength of the magnetic field.

[0034] S63: Combine the theoretical speed of the fan, the real-time speed of the fan, the reference current of the fan, the real-time current of the fan, and the magnetic field strength compensation coefficient to construct a fan dynamic balance model; Wherein, the expression of the fan dynamic balance model is: ; In the formula, Indicates the commutation angle; Indicates the magnetic field strength compensation constant; Indicates the reference current of the fan; Indicates the real-time current of the fan; Indicates the real-time speed of the fan; Indicates the actual commutation angle constant.

[0035] S64: Based on the comparison result, use the fan dynamic balance model to calculate and adjust the commutation angle of the automobile fan, realize the compensation of the real-time speed of the fan to the theoretical speed of the fan, and make the automobile fan reach the best operating state.

[0036] Embodiment 2 As Figure 2 shown, the embodiment provides a complex signal multi-drive intelligent recognition motor speed control system, comprising a signal acquisition and recognition module, a speed calculation module, a discrimination and adjustment module.

[0037] Specifically, the signal acquisition and recognition module acquires automobile fan signals; based on the automobile fan signals, signal effectiveness recognition is performed to obtain effective signals; based on the effective signals, signal type recognition is performed to determine the signal type. Specifically, the speed calculation module, based on the recognized signal type, calls a speed function corresponding to the signal type to obtain a fan simulated speed corresponding to the signal type; real-time acquisition of environmental temperature and automobile fan internal temperature is performed, and an environmental temperature acquisition speed compensation model and a fan temperature acquisition speed compensation model are fitted and constructed, and combined with the fan simulated speed corresponding to the signal type, a fan theoretical speed corresponding to the signal type is determined. Specifically, the discrimination and adjustment module compares the fan real-time speed and the fan theoretical speed to obtain a comparison result, and combined with the fan current and the magnetic field strength, the fan real-time speed is compensated to the fan theoretical speed by using a fan dynamic balance model, so that the automobile fan performs a commutation angle adjustment and reaches an optimal operating state.

[0038] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily mean the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0039] Although the embodiments of the present application have been shown and described above, it should be understood that the above-described embodiments are exemplary and should not be construed as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above-described embodiments within the scope of the present application.

Claims

1. A method for intelligent identification and motor speed control based on complex signals and multiple drives, characterized in that, include: Acquire automotive fan signal; Based on the automotive fan signal, the validity of the signal is identified to obtain the valid signal; Based on the valid signal, the signal type is identified and determined. Based on the identified signal type, the corresponding speed function for that signal type is called to obtain the simulated speed of the wind turbine corresponding to that signal type; Real-time acquisition of ambient temperature and the internal temperature of the car fan; fitting and constructing an ambient temperature acquisition speed compensation model and a fan temperature acquisition speed compensation model; and combining the simulated fan speed corresponding to the signal type to determine the theoretical fan speed corresponding to the signal type. By comparing the real-time speed of the fan with its theoretical speed, the comparison results are obtained. Combined with the fan current and magnetic field strength, the real-time speed of the fan is compensated to the theoretical speed using a dynamic balance model, so that the commutation angle of the car fan can be adjusted and the optimal operating state can be achieved.

2. The method for intelligent identification of motor speed control based on complex signals and multiple drives according to claim 1, characterized in that, The process of identifying the validity of signals based on automotive fan signals to obtain valid signals includes: Based on the automotive fan signal, obtain the peak value of the fan signal, the start time of the fan signal, and the end time of the fan signal; Calculate the area of ​​the wind turbine signal waveform by combining the peak value of the wind turbine signal, the start time of the wind turbine signal, and the end time of the wind turbine signal; The area of ​​the wind turbine signal waveform is compared with the effective area domain, and the wind turbine signal that falls within the effective area domain is taken as the effective signal.

3. The method for intelligent identification and motor speed control based on complex signals and multiple drives according to claim 1, characterized in that, The process of identifying signal type based on valid signals and determining the signal type includes: Based on the valid signals within a fixed time period, obtain the minimum and maximum levels of the valid signals; When both the minimum and maximum voltage levels are in the high voltage range, the current signal is determined to be an analog signal. When the minimum level is in the low level range, the maximum level is in the high level range, and the variance of the duration of multiple consecutive high levels is less than a preset threshold, the current signal is determined to be a digital signal. When the minimum level is in the low level range, the maximum level is in the high level range, and the variance of the duration of multiple consecutive high levels is not less than a preset threshold, the current signal is determined to be a LIN signal.

4. The method for intelligent identification of motor speed control based on complex signals and multiple drives according to claim 1, characterized in that, Real-time ambient temperature and the internal temperature of the car's fan are collected. An ambient temperature acquisition speed compensation model and a fan temperature acquisition speed compensation model are constructed. Combined with the simulated fan speed corresponding to the signal type, the theoretical fan speed corresponding to the signal type is determined, including: Multiple ambient temperatures are continuously collected within a fixed time period. An ambient temperature fitting function is constructed, and an ambient temperature acquisition speed compensation model is built based on the ambient temperature fitting function to determine the ambient temperature acquisition speed compensation coefficient. The internal temperature of multiple automotive fans was continuously collected within a fixed time period. A fan temperature fitting function was constructed, and based on the fan temperature fitting function, a fan temperature acquisition speed compensation model was constructed to determine the ambient temperature acquisition speed compensation coefficient. Based on the ambient temperature acquisition speed compensation coefficient and the simulated fan speed corresponding to the signal type, the theoretical fan speed corresponding to the signal type is determined.

5. The method for intelligent identification of motor speed control based on complex signals and multiple drives according to claim 4, characterized in that, The expression for the ambient temperature fitting function is: ； In the formula, Indicates the first An ambient temperature value, , This indicates the total number of ambient temperature samples collected. This represents the ambient temperature fitting function; Indicates the first Ambient temperature collection time; The expression for the environmental temperature acquisition rate compensation model is: ； In the formula, This represents the environmental temperature acquisition rate compensation coefficient. Indicates the ambient temperature compensation coefficient; This represents the compensation coefficient for the rate of change of ambient temperature. The expression for the fan temperature fitting function is: ； In the formula, Indicates the first The internal temperature value of the fan. , This indicates the total number of temperature readings collected inside the fan. This represents the fitting function for the internal temperature of the fan. Indicates the first Temperature acquisition time for each fan's internal temperature; The expression for the fan temperature acquisition speed compensation model is: ； In the formula, This indicates the compensation coefficient for the fan temperature acquisition speed; This indicates the internal temperature compensation coefficient of the fan; This represents the compensation coefficient for the rate of temperature change inside the fan; The expression for the theoretical rotational speed of the wind turbine is: ； In the formula, Indicates the theoretical rotational speed of the fan; This represents the rotational speed function corresponding to the analog signal. This represents the rotational speed function corresponding to the digital signal. This represents the rotational speed function corresponding to the LIN signal.

6. The method for intelligent identification of motor speed control based on complex signals and multiple drives according to claim 1, characterized in that, The comparison between the real-time speed and the theoretical speed of the fan is used to obtain the comparison results. Combined with the fan current and magnetic field strength, a dynamic balance model is used to compensate the real-time speed of the fan to the theoretical speed, enabling the automotive fan to adjust its reversing angle and achieve optimal operating conditions. This includes: Compare the real-time speed of the fan with the theoretical speed of the fan to obtain the comparison results; Real-time acquisition of magnetic field strength, combined with effective signals, to construct a magnetic field strength compensation model and determine the magnetic field strength compensation coefficient; A dynamic balance model of the wind turbine is constructed by combining the theoretical speed of the wind turbine, the real-time speed of the wind turbine, the reference current of the wind turbine, the real-time current of the wind turbine, and the magnetic field strength compensation coefficient. Based on the comparison results, the commutation angle of the automobile fan is calculated and adjusted using the dynamic balance model of the fan, so as to achieve compensation between the real-time speed of the fan and the theoretical speed of the fan, and enable the automobile fan to reach the optimal operating state.

7. The method for intelligent identification of motor speed control based on complex signals and multiple drives according to claim 6, characterized in that, The real-time acquisition of magnetic field strength, combined with effective signals, constructs a magnetic field strength compensation model and determines the magnetic field strength compensation coefficients, including: Based on the effective signal, the waveform and back EMF waveform of the automotive fan are acquired in real time to determine the actual frequency of the automotive fan and the actual frequency of the automotive fan back EMF waveform. The actual magnetic field strength and the reference magnetic field strength are obtained. Combined with the actual frequency of the back EMF waveform of the automobile fan, a magnetic field strength compensation model is constructed, and the magnetic field strength compensation coefficient is determined.

8. The method for intelligent identification of motor speed control based on complex signals and multiple drives according to claim 7, characterized in that, The expression for the magnetic field strength compensation model is: ； In the formula, Indicates the magnetic field compensation coefficient; This represents the commutation frequency constant of the automotive fan; This indicates the actual frequency of the back EMF waveform of the automotive fan. This indicates the actual frequency of the back EMF waveform of the automotive fan. Indicates the actual frequency of the car's fan; Represents the magnetic field strength constant; Indicates the actual strength of the magnetic field; It represents the reference strength of the magnetic field.

9. The method for intelligent identification of motor speed control based on complex signals and multiple drives according to claim 8, characterized in that, The expression for the dynamic balance model of the wind turbine is: ； In the formula, Indicates the reversal angle; This represents the magnetic field strength compensation constant; Indicates the fan reference current; Indicates the real-time current of the fan; Indicates the real-time speed of the fan; This represents the actual commutation angle constant.

10. A system for implementing the complex signal multi-drive intelligent identification motor speed control method of claim 1, characterized in that, include: The signal acquisition and recognition module acquires signals from the car's fan. Based on the automotive fan signal, signal validity is identified to obtain valid signals; based on the valid signals, signal type is identified to determine the signal type. The speed calculation module, based on the identified signal type, calls the corresponding speed function for the signal type to obtain the simulated speed of the fan corresponding to the signal type; it collects the ambient temperature and the internal temperature of the car fan in real time, fits and constructs an ambient temperature acquisition speed compensation model and a fan temperature acquisition speed compensation model, and combines them with the simulated speed of the fan corresponding to the signal type to determine the theoretical speed of the fan corresponding to the signal type. The discrimination and adjustment module compares the real-time speed of the fan with the theoretical speed of the fan, obtains the comparison result, and combines the fan current and magnetic field strength. Using the dynamic balance model of the fan, it compensates the real-time speed of the fan to the theoretical speed of the fan, so that the commutation angle of the car fan can be adjusted and the optimal operating state can be achieved.

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