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CN-122009050-A - Vehicle heat dissipation control method and device based on fuzzy control, electronic equipment, storage medium and vehicle

CN122009050ACN 122009050 ACN122009050 ACN 122009050ACN-122009050-A

Abstract

The application provides a vehicle heat dissipation control method based on fuzzy control, which belongs to the field of vehicle heat management, and comprises the steps of firstly determining a current heat dissipation demand index based on acquired vehicle working condition parameters, namely determining a current heat dissipation level required by a vehicle, further obtaining an optimal grid opening and an optimal fan rotating speed by inquiring a preset fuzzy rule base, finally controlling the grid to reach the optimal grid opening, and controlling the fan to reach the optimal fan rotating speed, so that the vehicle heat dissipation can be regulated according to actual working conditions, and the vehicle is prevented from overheating.

Inventors

  • ZHANG WEI

Assignees

  • 奇瑞汽车股份有限公司

Dates

Publication Date
20260512
Application Date
20260107

Claims (10)

  1. 1. A vehicle heat dissipation control method based on fuzzy control, the method comprising: Acquiring vehicle working condition parameters; Determining a current heat dissipation demand index according to the vehicle working condition parameters; inputting the vehicle working condition parameters and the current heat dissipation demand index into a preset fuzzy rule base to obtain the output optimal grid opening and optimal fan rotating speed; And generating a corresponding control instruction according to the optimal grid opening and the optimal fan rotating speed, wherein the control instruction is used for controlling the grid to reach the optimal grid opening and controlling the fan to reach the optimal fan rotating speed.
  2. 2. The vehicle heat dissipation control method based on fuzzy control of claim 1, wherein the obtaining the vehicle operating condition parameters comprises: collecting vehicle working condition signals by using a sensor; and performing first-order low-pass filtering processing on the vehicle working condition signals to obtain the vehicle working condition parameters.
  3. 3. The fuzzy control-based vehicle heat dissipation control method of claim 1, wherein the vehicle operating parameters include a current engine temperature, a current motor temperature, a current battery temperature, and a current compressor pressure, and wherein determining a current heat dissipation demand index from the vehicle operating parameters comprises: According to the vehicle working condition parameters, the current heat dissipation demand index is determined by adopting the following weighted summation model: Wherein the method comprises the steps of Representing the current heat dissipation demand index, Representing the current engine temperature in question, Representing the optimum temperature of the engine, Representing the current motor temperature in question, Representing the optimum temperature of the motor, Representing the current temperature of the battery in question, Representing the optimal temperature of the battery, Representing the current compressor pressure in question, Representing the optimum pressure of the compressor, Is a normalization function of the engine when < The function value is 0 when The function value is dependent on The absolute value of the difference between them increases linearly, Is a motor normalization function when < The function value is 0 when The function value is dependent on The absolute value of the difference between them increases linearly, Is a battery normalization function when < The function value is 0 when The function value is dependent on The absolute value of the difference between them increases linearly, Is a normalized function of the compressor when < The function value is 0 when The function value is dependent on And The absolute value of the difference value is increased instead of being linearly increased, and the increasing rate of the function value is increased along with And The absolute value of the difference between them increases, Is a preset first weight coefficient, Is a preset second weight coefficient, Is a preset third weight coefficient which is set, Is a preset fourth weight coefficient.
  4. 4. The vehicle heat dissipation control method based on fuzzy control of claim 3, wherein the first weight coefficient is preset Preset said second weight coefficient Preset said third weight coefficient And the fourth preset weight coefficient Representing the priority and influence degree of the engine, the motor, the battery and the air conditioning system in the heat dissipation requirement respectively, and corresponding the first weight coefficient when the vehicle is in the motion mode And the second weight coefficient Increasing, when the vehicle is in the quick charge mode, the corresponding third weight coefficient Increasing.
  5. 5. The vehicle heat dissipation control method based on fuzzy control of claim 1, wherein the vehicle condition parameter further includes a current vehicle speed, the fuzzy rule base includes a first correspondence among the heat dissipation demand index, the vehicle speed, and the grid opening, the first value range of the heat dissipation demand index is a first value range, the first value range is blurred into a first low subset, a first medium subset, and a first high subset by a triangle membership function, the value range of the vehicle speed is a second value range, the second value range is blurred into a second low subset, a second medium subset, and a second Gao Ziji by a triangle and a trapezoid membership function, the value range of the grid opening is a third value range, the third value range is blurred into a third closed subset, a third low subset, a third medium subset, a third high subset, and a third full open subset by a triangle and a trapezoid membership function, and the first correspondence is as follows: When the input heat dissipation demand index falls into the first low subset and the input vehicle speed falls into the second low subset, determining that the output grid opening is in the third closed subset; When the input heat dissipation demand index falls into the first low subset and the input vehicle speed falls into the second medium subset, determining that the output grid opening is in the third closed subset; When the input heat dissipation demand index falls into the first low subset and the input vehicle speed falls into the second high subset, determining that the output grid opening is in the third closed subset; When the input heat dissipation demand index falls into the first middle subset and the input vehicle speed falls into the second low subset, determining that the output grid opening is in the third sub-set; when the input heat dissipation demand index falls into the first middle subset and the input vehicle speed falls into the second middle subset, determining that the output grid opening is in the third low subset; when the input heat dissipation demand index falls into the first middle subset and the input vehicle speed falls into the second high subset, determining that the output grid opening is in the third closed subset; When the input heat dissipation demand index falls into the first high subset and the input vehicle speed falls into the second low subset, determining that the output grid opening is in the third full-opening subset; when the input heat dissipation demand index falls into the first high subset and the input vehicle speed falls into the second medium subset, determining that the output grid opening is in the third high subset; when the input heat dissipation demand index falls into the first high subset and the input vehicle speed falls into the second high subset, determining that the output grid opening is in the third subset, Inputting the vehicle working condition parameters and the current heat dissipation demand index into a preset fuzzy rule base to obtain the output optimal grid opening and the output optimal fan rotating speed, wherein the method further comprises the following steps: and defuzzifying the subset of the output grid opening degrees to obtain the output optimal grid opening degrees.
  6. 6. The vehicle heat dissipation control method based on fuzzy control of claim 5, wherein the vehicle condition parameters further include a current grille opening, the fuzzy rule base includes a second correspondence among the heat dissipation demand index, the vehicle speed, the grille opening, and a fan rotation speed, the fan rotation speed range is a fourth value range, the fourth value range is blurred into a fourth closed subset, a fourth low subset, a fourth medium subset, a fourth high subset, and a fourth full open subset by triangle and trapezoid membership functions, the inputting the vehicle condition parameters and the current heat dissipation demand index into a preset fuzzy rule base, and obtaining an output optimal grille opening and an output optimal fan rotation speed further includes: Inputting the heat dissipation demand index, the vehicle speed and the grid opening into the second corresponding relation to obtain a subset of the output fan rotating speed; And defuzzifying the subset of the output fan rotating speeds to obtain the output optimal fan rotating speed.
  7. 7. A vehicle heat dissipation control device based on fuzzy control, characterized in that the device comprises: The acquisition module is configured to acquire vehicle working condition parameters; The determining module is configured to determine a current heat dissipation demand index according to the vehicle working condition parameters; The fuzzy calculation module is configured to input the vehicle working condition parameters and the current heat dissipation demand index into a preset fuzzy rule base to obtain the output optimal grid opening and the output optimal fan rotating speed; The control module is configured to generate corresponding control instructions according to the optimal grid opening and the optimal fan rotating speed, wherein the control instructions are used for controlling the grid to reach the optimal grid opening and controlling the fan to reach the optimal fan rotating speed.
  8. 8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the fuzzy control based vehicle heat dissipation control method of any one of claims 1-6 when executing the computer program.
  9. 9. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the vehicle heat radiation control method based on fuzzy control as claimed in any one of claims 1 to 6.
  10. 10. A vehicle comprising the electronic device of claim 8.

Description

Vehicle heat dissipation control method and device based on fuzzy control, electronic equipment, storage medium and vehicle Technical Field The application relates to the field of automobile heat management, in particular to a vehicle heat dissipation control method and device based on fuzzy control, electronic equipment, a storage medium and a vehicle. Background The active air inlet grille and the cooling fan are both used for radiating heat of a heat generating component of the vehicle, so that irreversible damage caused by overheating is avoided. In existing active grille and cooling fan control strategies, the control strategy typically relies on a fixed threshold, and the grille and cooling fan are typically controlled independently of each other. The control depending on the fixed threshold value can cause poor adaptability to dynamically-changed working conditions (such as vehicle speed, load and battery SOC), and the independent control of the active air inlet grille and the cooling fan can cause unreasonable airflow organization and higher cooling energy consumption. In addition, the existing control strategy cannot comprehensively consider the coupling heat dissipation requirements of multiple heat sources such as a motor, an engine, a battery and the like, and local overheat risks are easily caused. Disclosure of Invention In view of the above, the present application provides a vehicle heat dissipation control method based on fuzzy control, which can adjust vehicle heat dissipation according to actual working conditions. In one aspect, the application provides a vehicle heat dissipation control method based on fuzzy control, which comprises the following steps: Acquiring vehicle working condition parameters; determining a current heat dissipation demand index according to the vehicle working condition parameters; inputting the vehicle working condition parameters and the current heat dissipation demand index into a preset fuzzy rule base to obtain the output optimal grid opening and the output optimal fan rotating speed; and generating a corresponding control instruction according to the optimal grid opening and the optimal fan rotating speed, wherein the control instruction is used for controlling the grid to reach the optimal grid opening and controlling the fan to reach the optimal fan rotating speed. Optionally, obtaining the vehicle operating condition parameter includes: collecting vehicle working condition signals by using a sensor; and performing first-order low-pass filtering processing on the vehicle working condition signals to obtain vehicle working condition parameters. Optionally, the vehicle operating condition parameters include a current engine temperature, a current motor temperature, a current battery temperature, and a current compressor pressure, and determining the current heat dissipation demand index according to the vehicle operating condition parameters includes: According to the working condition parameters of the vehicle, the current heat dissipation demand index is determined by adopting the following weighted summation model: Wherein the method comprises the steps of Representing the current heat dissipation demand index,Representing the current engine temperature of the engine,Representing the optimum temperature of the engine,Representing the current temperature of the motor,Representing the optimum temperature of the motor,Representing the current temperature of the battery,Representing the optimal temperature of the battery,Representing the current compressor pressure and,Representing the optimum pressure of the compressor,Is a normalization function of the engine when<The function value is 0 whenThe function value is dependent onThe absolute value of the difference between them increases linearly,Is a motor normalization function when<The function value is 0 whenThe function value is dependent onThe absolute value of the difference between them increases linearly,Is a battery normalization function when<The function value is 0 whenThe function value is dependent onThe absolute value of the difference between them increases linearly,Is a normalized function of the compressor when<The function value is 0 whenThe function value is dependent onAndThe absolute value of the difference value is increased instead of being linearly increased, and the increasing rate of the function value is increased along withAndThe absolute value of the difference between them increases,Is a preset first weight coefficient,Is a preset second weight coefficient,Is a preset third weight coefficient which is set,Is a preset fourth weight coefficient. Optionally, a preset first weight coefficientA preset second weight coefficientPreset third weight coefficientAnd a preset fourth weight coefficientRepresenting the priority and influence degree of the engine, the motor, the battery and the air conditioning system in the heat dissipation requirement respectively, corresponding first weight