A semiconductor refrigeration system

Abstract

The present invention discloses a semiconductor refrigeration system, which relates to the technical field of semiconductor refrigeration. The system comprises the following components: an environmental sensing unit: a temperature sensor is used to monitor the temperature data of the environment in real time, a sliding average filter is used to pre-process the temperature data to eliminate noise and fluctuation, and the processed data is transmitted to a central processing unit. Through real-time monitoring and remote control, the present invention enables users to grasp the semiconductor refrigeration situation at any time and make precise adjustments as needed. The system adopts advanced PWM current control algorithms and optimal control algorithms to achieve precise control of refrigeration power and effectively save energy. The application of the sliding average filter further improves the accuracy of data processing, reduces the influence of noise and fluctuation, and provides strong technical support for semiconductor refrigeration.

Description

Technical Field

[0001] The invention relates to the technical field of semiconductor refrigeration, in particular to a semiconductor refrigeration system. Background Art

[0002] Traditional refrigeration systems often rely on simple switch controls or fixed preset values ​​for regulation. This method cannot achieve accurate prediction and real-time response to ambient temperature. When environmental parameters change, they often respond slowly and cannot be adjusted quickly to meet actual needs, which to some extent affects the comfort and efficiency of use.

[0003] Traditional control systems still need to be improved in terms of intelligence and automation levels. With the continuous development of the Internet of Things and artificial intelligence technologies, users have put forward higher requirements for the intelligence and automation levels of control systems. Existing control systems often lack the application of these advanced technologies, and are unable to realize intelligent functions such as remote monitoring and automatic adjustment, and cannot meet the actual needs of users.

[0004] Therefore, in view of the deficiencies and shortcomings of the prior art, the present invention proposes a semiconductor refrigeration system to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to make up for the shortcomings of the prior art and to provide a semiconductor refrigeration system, which can realize real-time monitoring and precise control of the cold storage environment through semiconductor refrigeration technology, environmental perception, central processing and remote control, use temperature sensors and collect data, calculate the optimal refrigeration power through intelligent algorithms, and accurately adjust the refrigeration effect through PWM current control algorithms. Users can remotely monitor and adjust the cold storage environment through mobile phones and computers, thereby improving the convenience and efficiency of cold storage management.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a semiconductor refrigeration system, which includes the following components:

[0007] Environmental sensing unit: uses temperature sensors to monitor the temperature of the environment in real time, uses a sliding average filter to pre-process the temperature data, and transmits the processed data to the central processing unit;

[0008] Central processing unit: Receives data transmitted by the environmental sensing unit, processes and analyzes it, predicts future changes in temperature status through the time series prediction model, uses the difference method to convert the data into a stationary series, uses the autocorrelation function ACF and partial autocorrelation function PACF to determine the parameters (p, d, q) of the ARIMA model, and uses the maximum likelihood estimation to estimate the constant term c and autoregressive coefficient of the ARIMA model , moving average coefficient , the mathematical expression of the ARIMA model is: ,in: is the observed value at time t, is the error term. Combined with the real-time sensed temperature, an intelligent algorithm is used to calculate the optimal cooling power based on the predicted future temperature. and real-time temperature sensing , calculate the temperature deviation , the mathematical expression is: , initialize the three variables of the PID controller: proportional term P, integral term I and differential term D, calculate the proportional term: multiply the temperature deviation e(t) by the proportional coefficient , the mathematical expression is: , calculate the integral term: convert the temperature deviation The integral over time is multiplied by the integration factor , the mathematical expression is: , calculate the differential term: calculate the rate of change of temperature deviation e(t) , multiplied by the differential coefficient , the mathematical expression is: , calculate the total control amount: add the proportional term P, the integral term I and the differential term D to get the total control amount , the mathematical expression is: , the calculated total control quantity Convert into control instructions and send to the semiconductor temperature control core, monitor the execution of the semiconductor temperature control core, receive feedback data from the semiconductor temperature control core, and adjust the control strategy according to the feedback data;

[0009] Semiconductor temperature control core: using semiconductor refrigeration technology, by accurately controlling the size and direction of the current, to achieve the refrigeration function, through the built-in temperature sensor or receive the temperature data of the environmental sensing unit;

[0010] Remote control module: communicates with the user terminal through Internet technology, receives remote control instructions sent by the user terminal, transmits them to the central processing unit, and sends real-time temperature data to the user terminal;

[0011] User interface: Users access the user interface through mobile phones and computers to view real-time temperature data, historical data and the execution of control commands, set temperature thresholds according to needs, and send remote control commands to adjust the temperature.

[0012] Furthermore, the environment sensing unit uses a temperature sensor to measure the ambient temperature through a thermoelectric method, converts the collected data into an electrical signal, converts the electrical signal into a digital signal through an analog-to-digital converter ADC, and pre-processes the collected digital signal, using a sliding average filter to eliminate noise and fluctuations. The mathematical expression of the sliding average filter is: ,in: is the index of the current time point, is the size of the filter window, is within the time window from arrive The processed temperature data is packaged into a standard data packet format and transmitted to the central processing unit via wired mode.

[0013] Furthermore, the semiconductor temperature control core receives temperature data from the environmental sensing unit, compares the current temperature value with the preset target temperature value, and triggers the cooling process if the temperature is higher than the target temperature. The current in the current drive circuit is adjusted through the PWM current control algorithm to achieve cooling control, so that the current passes through the cooling end of the semiconductor refrigerator. The temperature of the semiconductor refrigerator is monitored in real time through the built-in temperature sensor, and the PWM duty cycle is dynamically adjusted according to the real-time temperature collected data.

[0014] Furthermore, the semiconductor temperature control core adjusts the current size in the current driving circuit through the PWM current control algorithm, controls the semiconductor refrigeration work, determines the period T of the PWM signal based on hardware limitations, and sets the initial duty cycle D according to the initial refrigeration effect. The duty cycle represents the proportion of the high level in a cycle, and the mathematical expression of the duty cycle D is: ,in: is the duration of the high level. The PWM generator is used to generate a PWM signal according to the set period and duty cycle. By changing the duty cycle of the PWM signal, the average current in the current drive circuit is controlled. The average current calculation formula is: ,in: is the average current, is the maximum current. The temperature is monitored in real time through the temperature sensor, and the duty cycle of the PWM signal is dynamically adjusted according to the temperature change.

[0015] Furthermore, the semiconductor temperature control core uses an optimal control algorithm to dynamically adjust the duty cycle of the PWM signal, selects the duty cycle of the key variable PWM signal that affects the temperature, and establishes a performance indicator function that describes the relationship between temperature, current and PWM duty cycle. , performance indicator function for: ,in: is the running loss function, is the temperature, is the duty cycle of the PWM signal, and They are the start and end time of the control, The terminal loss function selects the indirect method to derive the conditions and equations for optimal control according to the system characteristics and control requirements, and dynamically adjusts the duty cycle of the PWM signal according to the real-time temperature data and cooling effect.

[0016] Furthermore, the remote control module inputs the remote control to be executed through the remote control application interface of the user terminal. The instructions are encoded through the network protocol and sent to the remote server. After receiving the instructions, the server verifies them. The instructions that pass the verification are forwarded to the central processing unit. The central processing unit parses the received instructions and executes corresponding operations. The sensor collects environmental data in real time, the central processing unit processes the collected data, and the processed data is sent to the remote server. The user terminal receives and displays the real-time environmental data.

[0017] Furthermore, the user interface is opened through a mobile phone or computer to log in. After successful login, the real-time data is converted into dynamic elements on the graphical interface. The user queries the historical data within a certain period of time. The user interface displays the temperature change trend. The user sets the temperature threshold according to needs. When the environmental data exceeds or falls below the set threshold, the system will send an alarm to notify the user. The user executes the remote control command, and the user interface sends the command to the server, which forwards it to the central processing unit for execution.

[0018] Compared with the prior art, this semiconductor refrigeration system has the following beneficial effects:

[0019] 1. The present invention realizes accurate prediction and efficient control of ambient temperature by integrating environmental perception, time series prediction and PID control algorithm. It can receive environmental data in real time, accurately predict future temperature using ARIMA model, calculate the optimal cooling power in combination with PID control algorithm, and realize precise control through semiconductor temperature control core. It not only improves cooling efficiency and reduces energy consumption, but also enhances the intelligence and automation level of the system, providing users with a more comfortable and energy-saving experience.

[0020] 2. Through real-time monitoring and remote control, the present invention enables users to grasp the semiconductor refrigeration situation at any time and make precise adjustments as needed. The system adopts advanced PWM current control algorithm and optimal control algorithm to achieve precise control of refrigeration power and effectively save energy. The application of sliding average filter further improves the accuracy of data processing, reduces the impact of noise and fluctuations, and provides strong technical support for semiconductor refrigeration.

[0021] Other advantages, objectives and features of the present invention will be set forth in part in the following description and, in part, will be apparent to those skilled in the art based on an examination of the following or may be taught from the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 The figure is a flow chart of a semiconductor refrigeration system. DETAILED DESCRIPTION

[0024] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] Embodiment 1:

[0026] This embodiment provides a semiconductor refrigeration system, which can adjust the refrigeration power in real time to adapt to changes in ambient temperature through PWM current control algorithm and optimal control algorithm, thereby improving refrigeration efficiency and control accuracy. The ARIMA model is used to predict temperature, providing a reliable basis for the control of refrigeration power. Users can view environmental data in real time and send control instructions through the remote control module and user interface to achieve intelligent and remote management.

[0027] The environmental sensing unit uses a temperature sensor to measure the ambient temperature through the thermoelectric method and converts it into an electrical signal. The electrical signal is converted into a digital signal through the analog-to-digital converter ADC. The collected digital signal is pre-processed and a sliding average filter is used to eliminate noise and fluctuations. The mathematical expression of the sliding average filter is: , improve the accuracy of the data, and transmit the processed temperature data to the central processing unit.

[0028] The central processing unit receives real-time temperature data from the environmental sensing unit, loads past temperature records, and predicts future temperatures through the ARIMA model. The data is converted into a stationary sequence using the difference method. The autocorrelation function ACF and partial autocorrelation function PACF are used to determine the parameters (p, d, q) of the ARIMA model. The maximum likelihood estimation MLE is used to estimate the constant term c and autoregressive coefficient of the ARIMA model. , moving average coefficient , the mathematical expression of the ARIMA model is: , the ARIMA model parameters are determined by the maximum likelihood estimation function , and The value of , its likelihood function is: , take its logarithm, and get the log-likelihood function as: , the parameters are determined by finding the maximum value of the log-likelihood function , and The established ARIMA model is used to predict the future temperature, and the predicted results are compared with the actual observed values. The performance of the model is optimized accordingly. According to the predicted future temperature and the real-time perceived temperature, the PID control algorithm is used to calculate the optimal cooling power.

[0029] The PID control algorithm is based on the predicted future temperature and real-time temperature sensing , calculate the temperature deviation , the mathematical expression is: , initialize the three variables of the PID controller: proportional term P, integral term I and differential term D, proportional coefficient The initial value is based on the system open-loop gain To determine, the calculation formula is: ,in is the adjustment step size, is a sign function, is the temperature deviation, the integral coefficient The initial value is based on the system time constant and the expected steady-state error To estimate, the calculation formula is: , differential coefficient It is used to reflect the rate of change of temperature deviation. Its initial value is based on the oscillation frequency of the system. and damping ratio To estimate, the formula is: , calculate the proportional term: multiply the temperature deviation e(t) by the proportional coefficient , the mathematical expression is: , calculate the integral term: convert the temperature deviation The integral over time is multiplied by the integration factor , the mathematical expression is: , calculate the differential term: calculate the rate of change of temperature deviation e(t) , and then multiply by the differential coefficient , the mathematical expression is: , calculate the total control amount: add the proportional term P, the integral term I and the differential term D to get the total control amount , the mathematical expression is: , the calculated total control quantity Convert it into control instructions and send it to the semiconductor temperature control core. Use the temperature sensor to read the current ambient temperature value and adjust the parameters of the PID controller according to the feedback data to optimize the control effect.

[0030] The semiconductor temperature control core monitors the ambient temperature through the built-in temperature sensor and compares it with the preset target temperature. When the temperature exceeds the target value, it triggers the cooling process and uses the PWM current control algorithm to dynamically adjust the current in the current drive circuit. The cooling effect of the semiconductor refrigerator is controlled by adjusting the duty cycle of the PWM signal. The temperature of the refrigerator is monitored in real time to ensure safe operation. The optimal control algorithm is used to dynamically adjust the PWM duty cycle based on real-time temperature data to achieve precise temperature control. The optimal control conditions are derived through performance indicator functions and indirect methods to ensure that the system can achieve the expected temperature control performance.

[0031] The user of the remote control module inputs the remote control to be executed through the remote control application interface of the user terminal, receives the remote control instructions sent by the user, and transmits them to the central processing unit. The central processing unit parses the received instructions and performs corresponding operations. The sensor collects environmental data in real time and sends it to the remote server through the central processing unit. The user terminal receives and displays the real-time environmental data of the cold storage.

[0032] Users can access the user interface through mobile phones and computers. The system converts real-time and historical data into charts. Users can set temperature thresholds according to needs and send remote control commands to adjust the cold storage environment. Feedback information is also provided to users to help them understand the execution status of the commands.

[0033] Embodiment 2:

[0034] A semiconductor refrigeration system in this embodiment particularly emphasizes the semiconductor temperature control core

[0035] The temperature sensor obtains the current temperature value in real time and compares the current temperature value with the preset target temperature value. If the current temperature is higher than the target temperature, the cooling process is triggered.

[0036] Set the target temperature value, the initial period (T) and the initial duty cycle (D) of the PWM signal. The mathematical expression of the duty cycle D is: Based on the set PWM signal period (T) and initial duty cycle (D), the PWM current control module generates a PWM signal, which controls the current in the current drive circuit and further controls the cooling effect of the semiconductor refrigeration plate.

[0037] The temperature sensor built into the semiconductor temperature control core monitors the temperature of the semiconductor refrigeration chip in real time to ensure that it operates within a safe temperature range. According to the real-time temperature data and cooling effect, the duty cycle of the PWM signal is dynamically adjusted through the optimal control algorithm to achieve more precise temperature control.

[0038] The duty cycle of the PWM signal is selected as the key variable, and a performance index function describing the relationship between temperature, current and PWM duty cycle is established. for: ,According to the system characteristics and control requirements, the indirect method is used to derive the conditions and equations for optimal control, and the duty cycle of the PWM signal is dynamically adjusted using the optimal control algorithm based on the real-time temperature data and cooling effect.

[0039] Carry out long-term operation tests in the actual system, observe and record the temperature control effect, and adjust the parameters of the optimal control algorithm according to the test results to ensure that the system can achieve the expected temperature control performance.

[0040] Embodiment three:

[0041] Based on the first and second embodiments, the specific process steps of the system are as follows:

[0042] (1) Real-time monitoring of the temperature data of the environment through temperature sensors;

[0043] (2) The collected temperature data is preprocessed through a sliding average filter to eliminate noise and fluctuations and improve data accuracy;

[0044] (3) The central processing unit receives the data transmitted by the environmental sensing unit, processes and analyzes the received data, and predicts the changes in future temperature conditions through the time series prediction model;

[0045] (4) Combined with the real-time sensed temperature, the optimal cooling power is calculated using an intelligent algorithm. Based on the cooling power calculation results, corresponding control instructions are generated;

[0046] (5) Control the current size and direction of the semiconductor temperature control core through PWM signal to achieve cooling function;

[0047] (6) Send remote control commands to the central processing unit through the remote control module to achieve remote monitoring and control of the refrigeration system;

[0048] (7) Users can view the real-time environmental data, historical data, and execution status of control instructions of the cold storage through the user interface, set temperature thresholds according to needs, and send remote control instructions to adjust the cold storage environment.

[0049] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A semiconductor refrigeration system, characterized in that: The system consists of the following components: Environmental sensing unit: uses temperature sensors to monitor the temperature of the environment in real time, uses a sliding average filter to pre-process the temperature data, and transmits the processed data to the central processing unit; Central processing unit: Receives data transmitted by the environmental sensing unit, processes and analyzes it, predicts future changes in temperature status through the time series prediction model, uses the difference method to convert the data into a stationary series, uses the autocorrelation function ACF and partial autocorrelation function PACF to determine the parameters (p, d, q) of the ARIMA model, and uses the maximum likelihood estimation to estimate the constant term c and autoregressive coefficient of the ARIMA model , moving average coefficient , the mathematical expression of the ARIMA model is: ,in: is the observed value at time t, is the error term. Combined with the real-time sensed temperature, the optimal cooling power is calculated using an intelligent algorithm based on the predicted future temperature. and real-time temperature sensing , calculate the temperature deviation , the mathematical expression is: , initialize the three variables of the PID controller: proportional term P, integral term I and differential term D, calculate the proportional term: multiply the temperature deviation e(t) by the proportional coefficient , the mathematical expression is: , calculate the integral term: convert the temperature deviation The integral over time is multiplied by the integration factor , the mathematical expression is: , calculate the differential term: calculate the rate of change of temperature deviation e(t) , multiplied by the differential coefficient , the mathematical expression is: , calculate the total control amount: add the proportional term P, the integral term I and the differential term D to get the total control amount , the mathematical expression is: , the calculated total control quantity Convert into control instructions and send to the semiconductor temperature control core, monitor the execution of the semiconductor temperature control core, receive feedback data from the semiconductor temperature control core, and adjust the control strategy according to the feedback data; Semiconductor temperature control core: using semiconductor refrigeration technology, by accurately controlling the size and direction of the current, to achieve the refrigeration function, through the built-in temperature sensor or receive the temperature data of the environmental sensing unit; Remote control module: communicates with the user terminal through Internet technology, receives remote control instructions sent by the user terminal, transmits them to the central processing unit, and sends real-time temperature data to the user terminal; User interface: Users access the user interface through mobile phones and computers to view real-time temperature data, historical data and the execution of control commands, set temperature thresholds according to needs, and send remote control commands to adjust the temperature.

2. A semiconductor refrigeration system according to claim 1, characterized in that: The environment sensing unit uses a temperature sensor to measure the ambient temperature through a thermoelectric method, converts the collected data into an electrical signal, converts the electrical signal into a digital signal through an analog-to-digital converter ADC, and pre-processes the collected digital signal, using a sliding average filter to eliminate noise and fluctuations. The mathematical expression of the sliding average filter is: ,in: is the index of the current time point, is the size of the filter window, is within the time window from arrive The processed temperature data is packaged into a standard data packet format and transmitted to the central processing unit via wired mode.

3. A semiconductor refrigeration system according to claim 1, characterized in that: The semiconductor temperature control core receives the temperature data of the environmental sensing unit, compares the current temperature value with the preset target temperature value, and triggers the cooling process if the temperature is higher than the target temperature. The PWM current control algorithm is used to adjust the current in the current drive circuit to achieve cooling control, so that the current passes through the cooling end of the semiconductor cooling chip. The temperature of the semiconductor cooling chip is monitored in real time through the built-in temperature sensor, and the PWM duty cycle is dynamically adjusted according to the real-time temperature collected data.

4. A semiconductor refrigeration system according to claim 3, characterized in that: The semiconductor temperature control core adjusts the current size in the current driving circuit through the PWM current control algorithm, controls the semiconductor refrigeration work, determines the period T of the PWM signal based on hardware limitations, and sets the initial duty cycle D according to the initial refrigeration effect. The duty cycle represents the proportion of the high level in a cycle, and the mathematical expression of the duty cycle D is: ,in: is the duration of the high level. The PWM generator is used to generate a PWM signal according to the set period and duty cycle. By changing the duty cycle of the PWM signal, the average current in the current drive circuit is controlled. The average current calculation formula is: ,in: is the average current, is the maximum current. The temperature is monitored in real time through the temperature sensor, and the duty cycle of the PWM signal is dynamically adjusted according to the temperature change.

5. A semiconductor refrigeration system according to claim 3, characterized in that: The semiconductor temperature control core uses the optimal control algorithm to dynamically adjust the duty cycle of the PWM signal, selects the duty cycle of the key variable PWM signal that affects the temperature, and establishes a performance indicator function that describes the relationship between temperature, current and PWM duty cycle. , performance indicator function for: ,in: is the running loss function, is the temperature, is the duty cycle of the PWM signal, and They are the start and end time of the control, The terminal loss function selects the indirect method to derive the conditions and equations for optimal control according to the system characteristics and control requirements, and dynamically adjusts the duty cycle of the PWM signal according to the real-time temperature data and cooling effect.

6. A semiconductor refrigeration system according to claim 1, characterized in that: The remote control module inputs the remote control to be executed through the remote control application interface of the user terminal. The instructions are encoded through the network protocol and sent to the remote server. After receiving the instructions, the server verifies them. The instructions that pass the verification are forwarded to the central processing unit. The central processing unit parses the received instructions and executes corresponding operations. The sensor collects environmental data in real time, and the central processing unit processes the collected data. The processed data is sent to the remote server, and the user terminal receives and displays the real-time environmental data.

7. A semiconductor refrigeration system according to claim 1, characterized in that: The user interface is opened through a mobile phone or computer to log in. After successful login, the real-time data is converted into dynamic elements on the graphical interface. The user queries the historical data within a certain period of time. The user interface displays the temperature change trend. The user sets the temperature threshold according to the needs. When the environmental data exceeds or falls below the set threshold, the system will send an alarm to notify the user. The user executes the remote control command, and the user interface sends the command to the server, which forwards it to the central processing unit for execution.

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