Intelligent fan control method and system based on Internet of Things and PWM speed regulation control

Abstract

The invention discloses an intelligent fan control method and system based on the Internet of Things and PWM speed regulation control. The intelligent fan control method comprises the steps that temperature and wind speed data are collected through a temperature controller installed on one side of a fan; uploading the collected data to an Internet of Things cloud platform, integrating the received data by the Internet of Things platform, and generating a fan rotating speed and temperature control instruction; after the temperature controller receives an instruction sent by the Internet of Things cloud platform, a corresponding PWM signal is generated through the PWM control module in combination with a self-adaptive adjustment mechanism, and the rotating speed of the fan is adjusted, so that accurate control over the temperature is achieved. The system efficiency is effectively improved, energy is saved, noise is reduced, accurate control over the rotating speed and temperature of the draught fan is achieved, the individual requirements of users are met, and the management efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent control of fans, and in particular to an intelligent control method and control system for fans based on the Internet of Things and PWM speed regulation control. Background Art

[0002] Traditional fan temperature control systems often rely on simple switch control or analog signal regulation, lacking intelligence and adaptive capabilities, resulting in low energy efficiency and significant noise problems. With the vigorous development of Internet of Things technology, fan control is gradually transforming towards intelligence and networking. However, most of the existing Internet of Things fan temperature control systems only stay at the level of data collection and remote monitoring, lacking efficient and accurate speed regulation mechanisms. PWM speed control technology, as an efficient and energy-saving speed regulation method, can achieve smooth adjustment of fan speed, but its application in the Internet of Things fan temperature control system has yet to be explored in depth. Summary of the invention

[0003] In order to overcome the above problems existing in the prior art, the present invention proposes a fan intelligent control method and control system based on the Internet of Things and PWM speed control.

[0004] The technical solution adopted by the present invention to solve the technical problem is: a fan intelligent control method based on the Internet of Things and PWM speed control, comprising the following steps: Step 1, collecting temperature and wind speed data through a thermostat installed on one side of the fan; Step 2, uploading the data collected in step 1 to the IoT cloud platform, which integrates the received data and generates fan speed and temperature control instructions; Step 3: After receiving the instruction sent by the IoT cloud platform, the thermostat generates a corresponding PWM signal through the PWM control module in combination with the adaptive adjustment mechanism, and adjusts the fan speed to achieve precise temperature control; The fan speed V in step 3 is expressed as: V=k×V max ×D new D new =sat(D old +u) Where k is the coefficient; V max is the maximum speed; sat is the limiter function; D old is the duty cycle of the previous moment, D new is the new duty cycle after PID adjustment, and u is the control quantity calculated based on the PID control algorithm.

[0005] In the above-mentioned intelligent control method for a fan based on the Internet of Things and PWM speed control, the specific calculation process of the control quantity calculated based on the PID control algorithm is: u=K p *e+K i *∫edt+K d *dt / de e=N desired −N actual Among them, the expected value of the fan speed N desired , actual speed N actual , K p is the proportionality coefficient, K i is the integration coefficient, K d is the differential coefficient.

[0006] In the above-mentioned intelligent control method for a fan based on the Internet of Things and PWM speed control, the expected value N of the fan speed is desired By outdoor temperature T out Adjustment, the specific method is: When T out >30℃, the fan runs at high speed, N desired =N max ; When 15℃≤T out ≤30℃, fan running at medium speed, N desired =k1*N max , k1 is the medium speed coefficient; When 0℃≤T out When the temperature is less than 15℃, the fan runs at low speed, N desired =k2*N max , k2 is the low speed coefficient.

[0007] In the above-mentioned intelligent control method for a fan based on the Internet of Things and PWM speed control, in step 2, the Internet of Things cloud platform is connected to the mobile app and the Web terminal, and the temperature is adjusted and the data is displayed in real time through the mobile app and the Web terminal.

[0008] A fan intelligent control system based on the Internet of Things and PWM speed control uses the above-mentioned fan intelligent control method based on the Internet of Things and PWM speed control, including a fan, a thermostat installed on one side of the fan, the thermostat has built-in temperature sensor, wind speed sensor, PWM module, and communication module, the temperature sensor and wind speed sensor monitor the temperature and wind speed in real time and upload the monitoring data to the Internet of Things platform through the communication module, the Internet of Things platform integrates the received data, and generates fan speed and temperature control instructions according to the temperature and speed set by the user, and the PWM module receives instructions from the Internet of Things platform through the communication module to adjust the fan speed.

[0009] The beneficial effect of the present invention is that the present invention effectively improves the system efficiency: through the combination of PWM speed control technology and the Internet of Things platform, accurate control of the fan speed and temperature is achieved, thereby improving the overall efficiency of the temperature control system.

[0010] Energy saving and noise reduction: PWM speed control technology can reduce the fan's energy consumption and noise at low-efficiency speeds, achieve energy saving and noise reduction effects, and improve user experience.

[0011] Intelligent self-adaptation: The thermostat can adaptively adjust the duty cycle and frequency of the PWM signal according to the real-time monitored ambient temperature, wind speed changes and user needs, to achieve precise control of the fan speed and temperature and meet the user's personalized needs.

[0012] Remote intelligent control: Through the Internet of Things platform, remote intelligent control of the thermostat is realized, which is convenient for users to manage the temperature control system anytime and anywhere and improve management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a circuit wiring diagram of an embodiment of the present invention. DETAILED DESCRIPTION

[0014] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0015] This embodiment discloses a fan intelligent control method and control system based on the Internet of Things and PWM speed control, which can be applied to refrigeration equipment. Figure 1 The system architecture of this embodiment includes: Internet of Things cloud platform: responsible for receiving, processing and analyzing data from the thermostat, generating evaporator fan speed and temperature control instructions, and providing remote control function.

[0016] Thermostat: Installed near the evaporator fan, with built-in temperature sensor, wind speed sensor, PWM control module and communication module. The thermostat monitors the ambient temperature and wind speed in real time, and adjusts the speed of the evaporator fan through PWM control technology, while interacting with the IoT cloud platform for data.

[0017] Evaporating fan: According to the instructions sent by the thermostat through the PWM signal, it adjusts its own speed to achieve precise temperature control.

[0018] The thermostat collects ambient temperature and wind speed data in real time through the built-in temperature sensor and wind speed sensor.

[0019] The collected data is uploaded to the IoT cloud platform via a wireless network. The cloud platform uses intelligent algorithms to process and analyze the data and generate fan speed and temperature control instructions.

[0020] After receiving the instructions sent by the cloud platform, the thermostat generates the corresponding PWM signal through the PWM control module to accurately adjust the speed of the evaporating fan to achieve precise temperature control.

[0021] Step 1, collecting temperature and wind speed data through a thermostat installed on one side of the evaporating fan; Step 2, uploading the data collected in step 1 to the IoT cloud platform, which integrates the received data and generates fan speed and temperature control instructions; Step 3: After receiving the instruction sent by the IoT cloud platform, the thermostat generates a corresponding PWM signal through the PWM control module in combination with the adaptive adjustment mechanism to adjust the speed of the evaporating fan to achieve precise temperature control.

[0022] The expression of the evaporator fan speed V in step 3 is: V = k × V max ×D new D new =sat(D old +u) Where V: actual speed of the evaporator fan; k: a correction factor used to consider the impact of motor characteristics and load conditions on the speed. max : Maximum speed of the fan when the PWM duty cycle is 100% (i.e. continuously powered). D new : The new duty cycle after some adjustment (such as PID control).

[0023] If we only look at it from the perspective of mathematical expressions, V and D new There is a linear relationship between them, because when k and V max When V is a constant, D new That is, if D new Increase or decrease a certain ratio, V will also increase or decrease by the same ratio (in k and V max unchanged).

[0024] However, in practical applications, this linear relationship may be affected by a variety of nonlinear factors, such as: Motor characteristics: The speed of the motor may not be completely linear, especially at low or high speeds, and may be affected by factors such as friction and magnetic field saturation.

[0025] Load changes: An increase or decrease in load will affect the speed of the motor, and this effect is usually nonlinear.

[0026] Supply voltage fluctuations: Small changes in supply voltage can result in significant changes in motor speed, and this relationship can also be non-linear.

[0027] Thermostat and PWM controller accuracy and response speed: The performance limitations of these devices may cause a deviation between the actual speed and the desired speed.

[0028] PID controller parameter setting: The parameters of the PID controller (proportional, integral, and differential coefficients) have an important influence on the response speed and stability of the system. Improper parameter settings may lead to nonlinear behavior.

[0029] Therefore, although from the mathematical expression V = k × V max ×D new It is linear, but in practical applications, due to the existence of the above nonlinear factors, this relationship may show nonlinear characteristics. In order to obtain more accurate control effects, it may be necessary to consider these nonlinear factors and adjust and optimize the control strategy accordingly.

[0030] The duty cycle (D) is the ratio of the high level time (Ton) in the PWM signal to the entire cycle time (Tperiod), that is: D=T on / T period Ideally, if we assume that the motor speed is proportional to the supply voltage, the fan speed (V) can be expressed as the maximum speed (V max ) is a function of the duty cycle. In a smaller duty cycle range, this relationship can be approximated to be linear, and the fan speed can be expressed as: V = V max ×D, V represents the actual speed of the fan, usually expressed in revolutions per minute (RPM) or other appropriate units; V max It indicates the maximum speed of the fan when the PWM duty cycle is 100% (i.e., continuously powered on); D indicates the duty cycle of the PWM signal, usually expressed as a percentage (0% to 100%).

[0031] In practical applications, the speed of the fan is also affected by many other factors, such as fluctuations in power supply voltage, thermal effects of the motor, changes in load, etc.

[0032] For a given maximum speed of 1800 rpm, V max Set it to 1800. Then, by adjusting the duty cycle D, the speed of the fan can be controlled.

[0033] The specific adaptive adjustment mechanism is: the thermostat can adaptively adjust the duty cycle and frequency of the PWM signal according to the real-time monitored ambient temperature, wind speed changes and user needs, so as to achieve precise control of the fan speed and temperature.

[0034] Adding PID (proportional-integral-differential) control to the fan speed control formula mentioned above can further improve the accuracy and stability of control. PID control is a commonly used feedback control strategy that calculates the control quantity based on the deviation between the current state of the system and the desired state to adjust the system output.

[0035] Defining Bias: First, we need to define the expected value N of the fan speed desired (based on outdoor temperature and preset control strategy) and actual speed N actual The deviation between: e=N desired −N actual Calculate PID control quantity: Next, the PID control algorithm is used to calculate the control quantity u, which will be used to adjust the duty cycle D: u=K p *e+K i *∫edt+K d *dt / de Among them, K p is the proportionality coefficient, K i is the integration coefficient, K d are differential coefficients. These coefficients need to be adjusted according to the characteristics of the fan and the control requirements.

[0036] Adjust the duty cycle: Apply the PID control amount u to adjust the duty cycle D. This can be achieved through a limiter (or saturation function) to ensure that the duty cycle D is within a reasonable range (for example, between 0 and 1): D new =sat(D old +u)

[0037] Where sat is a limiter function used to limit the duty cycle between 0 and 1. old is the duty cycle of the previous moment, D new It is the new duty cycle after PID adjustment.

[0038] Combined with temperature adjustment: In practical applications, it is necessary to adjust the temperature according to the outdoor temperature T out To adjust the expected value of fan speed N desired . This can be achieved using a piecewise function based on temperature, as described before:

[0039] When Tout >30℃, N desired =N max (High speed operation); When 15℃≤T out ≤30℃, N desired =k1*N max (Medium speed operation, k1 is the medium speed coefficient); When 0℃≤T out <15℃, N desired =k2*N max (Low speed operation, k2 is the low speed coefficient).

[0040] The above embodiments are only exemplary embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art may make various modifications or equivalent substitutions to the present invention within the essence and protection scope of the present invention, and such modifications or equivalent substitutions shall also be deemed to fall within the protection scope of the present invention.

Claims

1. A fan intelligent control method based on Internet of Things and PWM speed control, characterized in that: The steps include: Step 1, collecting temperature and wind speed data through a thermostat installed on one side of the fan; Step 2, uploading the data collected in step 1 to the IoT cloud platform, which integrates the received data and generates fan speed and temperature control instructions; Step 3: After receiving the instruction sent by the IoT cloud platform, the thermostat generates a corresponding PWM signal through the PWM control module in combination with the adaptive adjustment mechanism, and adjusts the fan speed to achieve precise temperature control; The fan speed V in step 3 is expressed as: V=k×V max ×D new D new =sat(D old +u) Where k is the coefficient; V max is the maximum speed; sat is the limiter function; D old is the duty cycle of the previous moment, D new is the new duty cycle after PID adjustment, and u is the control quantity calculated based on the PID control algorithm.

2. According to claim 1, a fan intelligent control method based on Internet of Things and PWM speed control is characterized in that: The specific calculation process of the control quantity calculated based on the PID control algorithm is: u=K p *e+K i *∫edt+K d *dt / de e=N desired −N actual Among them, the expected value of the fan speed N desired , actual speed N actual , K p is the proportionality coefficient, K i is the integration coefficient, K d is the differential coefficient.

3. The intelligent control method for a fan based on the Internet of Things and PWM speed control according to claim 2 is characterized in that: The expected value N of the fan speed desired By outdoor temperature T out Adjustment, the specific method is: When T out >30℃, the fan runs at high speed, N desired =N max ; When 15℃≤T out ≤30℃, fan running at medium speed, N desired =k1*N max , k1 is the medium speed coefficient; When 0℃≤T out <15℃, the fan runs at low speed, N desired =k2*N max , k2 is the low speed coefficient.

4. The intelligent control method for a fan based on the Internet of Things and PWM speed control according to claim 1 is characterized in that: In step 2, the IoT cloud platform is connected to the mobile app and the Web terminal, and the temperature is adjusted and the data is displayed in real time through the mobile app and the Web terminal.

5. A fan intelligent control system based on Internet of Things and PWM speed control, characterized in that: A fan intelligent control method based on the Internet of Things and PWM speed control according to any one of claims 1 to 4 is used, comprising a fan and a thermostat installed on one side of the fan, the thermostat having built-in temperature sensors, wind speed sensors, PWM modules, and communication modules, the temperature sensors and wind speed sensors monitor the temperature and wind speed in real time and upload the monitoring data to the Internet of Things platform through the communication module, the Internet of Things platform integrates the received data, and generates fan speed and temperature control instructions according to the temperature and speed set by the user, and the PWM module receives instructions from the Internet of Things platform through the communication module to adjust the fan speed.

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