PTC heater testing system, method and readable medium

Abstract

The present invention relates to the field of heater detection technology, and specifically to a PTC heater testing system, method and readable medium. The testing system comprises: a temperature sensor, used to detect the surface temperature and ambient temperature of the PTC heater; a current sensor and a voltage sensor, used to detect the current and voltage passing through the PTC heater; a controller, connected to the temperature sensor, the current sensor and the voltage sensor, and calculating the performance parameters and test data of the PTC heater based on the detected temperature, current and voltage data. The present invention provides an efficient, accurate and reliable PTC heater testing system and method, which solves many deficiencies in the prior art, provides a solid technical foundation and guarantee for the performance evaluation, optimal design and application promotion of PTC heaters, and has broad application prospects and significant commercial value.

Description

Technical Field

[0001] The present invention relates to the technical field of heater detection, and in particular to a PTC heater testing system, method and readable medium. Background Art

[0002] With the continuous growth of energy demand and the increasing awareness of environmental protection, electric heating technology, especially positive temperature coefficient (PTC) heater technology, has received more and more attention and application. PTC heater is an electric heating device that uses PTC material as a heating element. Its main feature is that it has a positive temperature coefficient characteristic that the resistance increases with increasing temperature. Compared with traditional resistive heating elements, PTC heaters have significant advantages in safety, energy efficiency and life, and have been widely used in many fields such as household appliances, automobile heating, industrial heating, etc.

[0003] Due to the limitations of materials and processes, existing PTC heaters will have some problems in actual use, such as low heating efficiency, imprecise temperature control, and high energy consumption. In order to improve the performance of PTC heaters, they must be tested and evaluated in detail. However, traditional PTC heater testing methods often have problems such as inaccurate test data, complex test processes, and low efficiency, which are difficult to meet the needs of modern efficient and accurate testing. Therefore, there is an urgent need for a new system and method that can perform comprehensive and accurate testing on PTC heaters in order to accurately evaluate their performance and discover potential problems, thereby promoting the further development and application of PTC heater technology. Summary of the invention

[0004] The present invention provides a PTC heater testing system, method and readable medium to solve the problems of inaccurate test data, complex test process and low efficiency in traditional PTC heater testing technology.

[0005] The technical solution of the present invention to solve the above technical problems is as follows:

[0006] A PTC heater testing system is provided, the testing system comprising:

[0007] A temperature sensor, used to detect the surface temperature and ambient temperature of the PTC heater;

[0008] A current sensor and a voltage sensor, used to detect the current and voltage passing through the PTC heater;

[0009] a controller connected to the temperature sensor, the current sensor and the voltage sensor, and calculating the performance parameters and test data of the PTC heater based on the detected temperature, current and voltage data;

[0010] a data storage device, connected to the controller, for storing the performance parameters and test data;

[0011] A display, connected to the controller, for displaying the performance parameters and test data;

[0012] an energy conversion module for calculating heat output and energy conversion efficiency based on electrical input of the PTC heater;

[0013] An environmental monitoring module, used to detect the influence of external environmental conditions on the performance of the PTC heater;

[0014] The fault diagnosis module is used to detect and diagnose the fault state of the PTC heater.

[0015] Furthermore, the controller includes a data processing module and an analysis module, wherein the data processing module is used to process raw data from the sensor, and the analysis module is used to analyze the processed data to obtain the performance parameters and test data, and the analysis module calculates the heat output based on the following formula:

[0016]

[0017] Where Q represents the heat output, P(t) represents the power that varies with time, V(t) represents the voltage that varies with time, I(t) represents the current that varies with time, and t represents time.

[0018] Furthermore, the data processing module includes a high-frequency sampling unit, which collects voltage data and current data of the PTC heater at a high sampling rate and performs frequency domain analysis on the voltage data and current data through fast Fourier transform.

[0019] Furthermore, the data processing module also includes a noise filtering unit and a signal enhancement unit, which processes the data in real time based on an adaptive filtering algorithm to remove environmental noise and signal interference.

[0020] Furthermore, the energy conversion module includes an energy balance calculation unit, and the balance calculation unit calculates the energy conversion efficiency using the following formula:

[0021]

[0022] Wherein, η represents the energy conversion efficiency, m represents the mass of the heater, c represents the specific heat capacity of the PTC heater material, dT / dt represents the rate of change of temperature over time, and P(t) represents the power that changes over time;

[0023] The energy balance calculation unit evaluates heating efficiency and energy loss by monitoring the power input and heat output of the PTC heater in real time.

[0024] Furthermore, the controller further includes an environmental compensation module for dynamically adjusting the performance parameters of the PTC heater based on changes in external environmental conditions to ensure the accuracy of the test results;

[0025] The environmental compensation module detects parameters such as ambient temperature, humidity and air pressure, and performs compensation based on the following formula:

[0026] Tc = Tm-k·(Te-Tm);

[0027] Wherein, Tc represents the compensated temperature, Tm represents the measured temperature, Te represents the ambient temperature, and k represents the compensation coefficient;

[0028] Based on the temperature, humidity and air pressure of the test environment, the compensation coefficient k is dynamically adjusted according to a preset environmental impact model.

[0029] Furthermore, a PTC heater testing method is provided, using the PTC heater testing system as described above, characterized in that the testing method comprises the following steps:

[0030] S100, connecting the PTC heater to the test system;

[0031] S200, start the PTC heater and detect its surface temperature and ambient temperature through the temperature sensor;

[0032] S300, detecting the current and voltage of the PTC heater through a current sensor and a voltage sensor;

[0033] S400, the controller receives and processes data from the sensor and calculates performance parameters of the PTC heater, including heat output and energy conversion efficiency;

[0034] S500, storing the calculated performance parameters in a data storage device and displaying them on a display;

[0035] S600, performing compensation based on external environmental conditions to ensure the accuracy of the test results;

[0036] S700: Run the fault diagnosis module to detect and diagnose the fault state of the PTC heater.

[0037] Furthermore, the testing method further comprises the following steps:

[0038] S101. Before starting the PTC heater, calibrate the sensor in advance to ensure the accuracy of the data. Calibrate using the following formula:

[0039] V cal =V meas+ΔV,I cal =I meas +ΔI;

[0040] Wherein, Vcal and Ical represent the calibrated voltage and current respectively, Vmeas and Imeas represent the measured voltage and current respectively, and ΔV and ΔI represent the calibration values.

[0041] Furthermore, the testing method further comprises the following steps:

[0042] S102, processing the sensor data by a filtering algorithm to remove noise and improve data accuracy, the filtering algorithm including but not limited to adaptive filtering and fast Fourier transform;

[0043] S103. After the test is completed, the test data and performance parameters are sent to an external device or a cloud server through a communication module for further analysis and storage.

[0044] Furthermore, a readable medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the PTC heater testing method described above is implemented.

[0045] The beneficial effects of the present invention are:

[0046] The present invention provides an efficient, accurate and reliable PTC heater testing system and method, which solves many deficiencies in the prior art, provides a solid technical foundation and guarantee for the performance evaluation, optimal design and application promotion of PTC heaters, and has broad application prospects and significant commercial value.

[0047] Specifically, the present invention can monitor the key parameters of the PTC heater (including surface temperature, ambient temperature, current and voltage) in real time and accurately by adopting high-precision temperature sensors, current sensors and voltage sensors, thereby significantly improving the accuracy of test data.

[0048] Furthermore, the controller of the present invention integrates an advanced data processing and analysis module, which can automatically process the collected data and calculate the performance parameters of the PTC heater such as heat output and energy conversion efficiency, thereby reducing the errors and complexity of manual operation and improving the efficiency and accuracy of the test.

[0049] Furthermore, the environmental monitoring module of the present invention can detect in real time the impact of external environmental conditions (such as temperature, humidity, air pressure, etc.) on the performance of the PTC heater, and dynamically adjust the test results through the environmental compensation module to ensure the accuracy and reliability of the test results, and is suitable for various complex test environments.

[0050] Furthermore, the energy conversion module and the energy balance calculation unit can accurately calculate the energy conversion efficiency of the heater, provide a comprehensive energy efficiency evaluation, and help optimize the design and performance of the PTC heater.

[0051] In addition, the system and method of the present invention have a simple and easy operation process. The user only needs to connect the PTC heater and start the system to automatically complete data collection, processing, analysis and display, which significantly improves the test efficiency.

[0052] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and implement it according to the contents of the specification, the following is a detailed description of the preferred embodiments of the present invention in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 A schematic diagram of an application environment of a test system in an embodiment of the present invention;

[0054] Figure 2 is an architecture diagram of a test system in one embodiment of the present invention;

[0055] Figure 3 is a schematic diagram of a controller according to an embodiment of the present invention;

[0056] Figure 4 is an architecture diagram of a data processing module in one embodiment of the present invention;

[0057] Figure 5 is a structural diagram of an energy conversion module in one embodiment of the present invention;

[0058] Figure 6 The process of the PTC heater testing method in one embodiment of the present invention is as follows: Figure 1 ;

[0059] Figure 7 The process of the PTC heater testing method in one embodiment of the present invention is as follows: Figure 2 ;

[0060] In the attached figure:

[0061] 1. Temperature sensor; 2. Current sensor; 3. Voltage sensor; 4. Controller; 5. Data storage device; 6. Display; 7. Energy conversion module; 8. Environmental monitoring module; 9. Fault diagnosis module. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention. In addition, it should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0063] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, an electrical connection, or mutual communication; it can be a direct connection, or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0064] The disclosure below provides many different embodiments or examples to implement different structures of the present invention. In order to simplify the disclosure of the present invention, the parts and settings of specific examples are described below. Of course, they are only examples, and the purpose is not to limit the present invention. In addition, the present invention can repeat reference numbers and / or reference letters in different examples, and this repetition is for the purpose of simplification and clarity, which itself does not indicate the relationship between the various embodiments and / or settings discussed.

[0065] The present invention provides the following preferred embodiments:

[0066] Embodiment 1

[0067] refer to Figure 1 and Figure 2 As shown, this embodiment provides a PTC heater testing system to achieve accurate testing and evaluation of the PTC heater. In order to achieve the above objectives, this embodiment describes in detail the various components of the testing system and their functions and effects.

[0068] In this embodiment, the temperature sensor 1 adopts a high-precision platinum resistance temperature sensor 1, model PT1000, which is used to detect the surface temperature and ambient temperature of the PTC heater. The PT1000 sensor has good linearity and high stability, and can provide accurate temperature measurement in a wide temperature range, ensuring the accuracy and reliability of the test data.

[0069] Furthermore, in order to detect the current and voltage passing through the PTC heater, this embodiment uses a Hall effect current sensor 2 and a high-precision voltage sensor 3. The Hall effect current sensor 2 is a LEM HASS 50-S model, which has high sensitivity and wide-band response characteristics, and can accurately detect the dynamic current changes of the PTC heater. The voltage sensor 3 is a TE Connectivity MHP35NL model, which has high precision and low drift characteristics, ensuring the accuracy of voltage measurement.

[0070] Furthermore, the controller 4 uses an STM32F4 series microcontroller 4, model STM32F407, and collects and processes temperature, current and voltage data in real time by connecting to the temperature sensor 1, the current sensor 2 and the voltage sensor 3. The controller 4 has a built-in data processing module and an analysis module. The data processing module includes a high-frequency sampling unit and a noise filtering unit, which collects data at a high sampling rate of up to 10kHz, and uses an adaptive filtering algorithm and a fast Fourier transform to process the data to remove environmental noise and signal interference. The analysis module calculates the performance parameters and test data of the PTC heater based on the collected data, such as heat output and energy conversion efficiency.

[0071] Furthermore, the data storage device 5 uses a large-capacity flash memory, model MX25L25635F, connected to the controller 4, for storing performance parameters and test data. The flash memory has high read and write speed and data preservation stability, ensuring safe storage and fast reading of test data.

[0072] Furthermore, the display 6 is a liquid crystal display screen, model TFT 320x240, connected to the controller 4, for real-time display of performance parameters and test data. The liquid crystal display screen has high brightness and high contrast, and can clearly display various test results, making it convenient for operators to monitor and record data.

[0073] In this embodiment, the energy conversion module 7 adopts a heat output calculation method based on thermocouple measurement. The thermocouple model is a K-type thermocouple, which is installed on the surface and environment of the PTC heater and is used to measure the heat output of the electrical input. By measuring the voltage, current and thermocouple temperature in real time, the energy conversion module 7 can accurately calculate the heat output and energy conversion efficiency of the PTC heater.

[0074] The environment monitoring module 8 uses a set of environment sensors, including temperature, humidity and air pressure sensors, which are SHT31 temperature and humidity sensor and BMP280 air pressure sensor. The environment monitoring module 8 monitors the external environment conditions in real time, analyzes the impact of the external environment on the performance of the PTC heater, and provides the controller 4 with environment compensation data.

[0075] Furthermore, the fault diagnosis module 9 is integrated in the controller 4, which monitors the data of each sensor in real time and adopts a fault detection algorithm based on rules and statistical models to timely detect and diagnose the fault status of the PTC heater, such as overheating, short circuit and sensor failure, and prompt the operator through the display 6 and the sound and light alarm module.

[0076] The benefit of this embodiment is that, through the organic combination of the above components, comprehensive and accurate testing and performance evaluation of the PTC heater are achieved. High-precision sensors and advanced data processing technology ensure the accuracy and reliability of test data; energy conversion module 7 and environmental monitoring module 8 provide comprehensive evaluation of heater performance and environmental compensation; fault diagnosis module 9 improves the safety and maintenance efficiency of the system. Through this embodiment, the problems of inaccurate data, complex process and low efficiency in the existing PTC heater testing technology can be effectively solved, providing strong technical support for the development and application of PTC heater technology.

[0077] Embodiment 2

[0078] refer to Figures 1 to 3 As shown, in order to solve the problem of inaccurate data processing in the traditional PTC heater test system, this embodiment further optimizes the structure of the controller 4, specifically including a data processing module and an analysis module. The organic combination of the data processing module and the analysis module enables the system to efficiently process the raw data from the sensor, and accurately calculate the performance parameters and test data of the PTC heater based on the processed data.

[0079] Specifically, the data processing module uses a high-performance digital signal processor DSP, model T ITMS320F28379D, which has powerful data processing capabilities and high-speed computing performance, and can process the raw data from temperature sensor 1, current sensor 2 and voltage sensor 3 in real time. The data processing module uses high-speed sampling with a sampling rate of up to 20kHz to ensure accurate capture of subtle changes in voltage and current signals. During the processing, the data processing module uses an adaptive filtering algorithm to filter the raw data in real time, remove environmental noise and electromagnetic interference, and ensure the purity of the signal and the accuracy of the data.

[0080] Furthermore, the data processing module also includes a fast Fourier transform (FFT) unit to perform frequency domain analysis on the collected voltage and current signals. This analysis process helps to identify the high-frequency components in the signal and further improve the accuracy of data processing. The signal data after preliminary processing is transmitted to the analysis module for further analysis and calculation.

[0081] Furthermore, the analysis module uses an advanced embedded processor, model ARM Cortex-M7, which can efficiently perform complex mathematical operations and data analysis tasks. The analysis module calculates the processed data based on the following formula:

[0082]

[0083] Where Q represents the heat output, P(t) represents the power that varies with time, V(t) represents the voltage that varies with time, I(t) represents the current that varies with time, and t represents time. By accurately calculating the product of voltage and current and integrating it over time, the analysis module can derive the heat output of the PTC heater in real time.

[0084] It is important to understand that the analysis module is not limited to the calculation of the above formula, but also has a variety of data analysis and processing functions. For example, the analysis module can perform statistical analysis on the heat output data, generate a curve chart of power changes over time, and analyze power fluctuations through built-in algorithms to provide a detailed heat output report.

[0085] Furthermore, in order to ensure the reliability of the analysis results, a data calibration unit is added in this embodiment. The data calibration unit uses a multi-point calibration method to accurately calibrate the sensor data. Specifically, the temperature sensor 1, the current sensor 2, and the voltage sensor 3 are calibrated by a standard reference source before use. During the calibration process, the deviation between the sensor measurement value and the standard value is recorded and stored in the non-volatile memory of the controller 4. During the actual test process, the calibration unit corrects the real-time measurement data according to the pre-stored calibration data to eliminate the system error of the sensor.

[0086] Furthermore, the analysis module also includes an energy conversion efficiency calculation unit. This unit calculates the energy conversion efficiency by comparing the heat output and the electrical input, and can monitor and evaluate the energy utilization of the PTC heater in real time. It should be understood that the various calculation units of the analysis module interact and synchronize data through the built-in high-speed data bus to ensure efficient and reliable data transmission between the units. Through the collaborative work of high-performance data processing and analysis modules, this embodiment can achieve a comprehensive and accurate performance evaluation of the PTC heater and provide detailed test data and analysis reports.

[0087] The benefit of this embodiment is that, by adopting a high-performance data processing and analysis module, real-time and accurate calculation of key performance parameters of the PTC heater is achieved, the reliability and accuracy of the test results are ensured, the overall performance of the PTC heater test system is improved, and a guarantee is provided for the research and development, optimization and application of the PTC heater.

[0088] Embodiment 3

[0089] refer to Figures 1 to 4 As shown, in order to solve the problems of insufficient sampling accuracy and data processing efficiency in the traditional PTC heater test system, this embodiment further optimizes the data processing module, especially introduces a high-frequency sampling unit and a fast Fourier transform FFT analysis unit to improve the acquisition and analysis accuracy of voltage and current data.

[0090] In this embodiment, the high-frequency sampling unit used in the data processing module is a high-performance analog-to-digital converter ADC, model AD9226, which has a 14-bit resolution and a sampling rate of 20MSPS (20 million samples per second), and can collect the voltage data and current data of the PTC heater with high precision. The high-frequency sampling unit can capture the instantaneous changes of voltage and current through high-speed sampling, ensuring the high fidelity of the collected data.

[0091] Furthermore, in order to ensure the stability of data acquisition, the high-frequency sampling unit also integrates a low-noise preamplifier, model INA128, to amplify the weak signal output by the sensor. The low noise characteristics and high common mode rejection ratio CMRR of the preamplifier ensure high-quality signal transmission, thereby reducing the impact of external electromagnetic interference on the collected data.

[0092] Furthermore, the collected voltage and current data are transmitted to the FFT analysis unit in the data processing module through a high-speed data bus. The FFT analysis unit uses a high-performance digital signal processor DSP, model TI TMS320C6678, which has powerful parallel processing capabilities and high-speed computing performance, and can perform frequency domain analysis on the collected data in real time. Through the fast Fourier transform FFT, the voltage and current data are converted from the time domain to the frequency domain, and their spectral components are analyzed, which helps to identify and filter out high-frequency noise and further improve the accuracy of the data.

[0093] It is important to understand that the FFT analysis unit is not only used for noise filtering, but also can extract the characteristic frequency of the signal to help analyze the harmonic components and transient response in the voltage and current signals. Through frequency domain analysis, a more comprehensive understanding of the dynamic performance and electrical characteristics of the PTC heater under different working conditions can be obtained.

[0094] In this embodiment, the data processing module also includes a real-time data cache unit, which uses a dual-port RAMDP-RAM, model IDT70V24, and the cache unit supports high-speed read and write operations to ensure the integrity and continuity of high-frequency sampling data during transmission and processing. The real-time data cache unit can temporarily store a large amount of collected data, providing sufficient time and space for subsequent data processing and analysis.

[0095] In order to further improve the overall performance of the system, this embodiment also integrates an adaptive noise filtering algorithm and a dynamic signal conditioning module. The adaptive noise filtering algorithm can dynamically adjust the filtering parameters according to the real-time collected environmental noise level to optimize the noise suppression effect. The dynamic signal conditioning module adjusts the sampling rate and amplification factor to adapt to signal changes under different working conditions to ensure the stability and consistency of data acquisition.

[0096] Through the optimized design of this embodiment, the data processing module realizes high-precision, high-frequency voltage and current data acquisition, as well as FFT-based frequency domain analysis, effectively improving the performance and data processing capabilities of the PTC heater test system. The benefit of this embodiment is that through the combination of advanced data processing technology and high-performance hardware, a comprehensive and accurate evaluation of the electrical characteristics of the PTC heater is achieved, providing important data support and technical guarantees for the optimization and improvement of the heater performance.

[0097] Through this embodiment, the data processing efficiency and test accuracy of the PTC heater test system can be significantly improved, the shortcomings of traditional test methods can be overcome, and a more reliable and efficient test solution can be provided for the research and development and application of PTC heaters.

[0098] Embodiment 4

[0099] refer to Figures 1 to 4 As shown, in order to solve the problem of reduced data accuracy due to environmental noise and signal interference in the PTC heater test system, the present embodiment further optimizes the data processing module, and especially introduces a noise filtering unit and a signal enhancement unit, and processes the data in real time based on an adaptive filtering algorithm to improve the accuracy and reliability of the data.

[0100] According to the high-frequency sampling unit and FFT analysis unit described in the above embodiments, the design of the data processing module has been further refined and enhanced. The noise filtering unit in the data processing module adopts advanced digital signal processing technology and integrates a high-performance digital signal processor DSP, model TI TMS320C6748. The DSP can efficiently execute complex adaptive filtering algorithms and perform noise filtering and signal enhancement on the collected voltage and current data in real time.

[0101] Furthermore, the noise filtering unit dynamically adjusts the filtering parameters through an adaptive filtering algorithm to remove environmental noise and signal interference. Specifically, the adaptive filtering algorithm can analyze the characteristics of the current environmental noise based on the real-time collected data, automatically adjust the frequency response of the filter, and optimize the filtering effect. For example, when the noise frequency component is relatively concentrated, the adaptive filter will enhance the suppression of this frequency band, thereby significantly reducing the impact of noise interference on the data.

[0102] It should be understood that the noise filtering unit is not limited to suppressing high-frequency noise, but also includes the effective filtering of low-frequency interference and electromagnetic interference. Through multi-level filtering and spectrum analysis, the noise filtering unit can comprehensively improve the purity of the signal and provide more reliable basic data for subsequent data processing and analysis.

[0103] Furthermore, the signal enhancement unit uses a high-precision signal amplifier, model AD8429, which has ultra-low noise and high gain characteristics and can accurately amplify weak voltage and current signals. The signal enhancement unit automatically adjusts the amplification factor according to the strength of the input signal through dynamic gain control to ensure that the signal can obtain the best amplification effect at different intensities. The amplified signal is sampled by a high-precision ADC to ensure that the data processing module obtains high-quality input data.

[0104] This embodiment also considers the coordination between the data processing module and other modules. The data processing module interacts with the analysis module through a high-speed data bus to ensure that the filtered high-quality data can be transmitted to the analysis module in a timely manner for further processing and calculation. Through efficient data transmission between modules, the entire system can achieve real-time data processing and performance evaluation, greatly improving the overall performance of the PTC heater test system.

[0105] It should be understood that this embodiment also combines an environmental monitoring unit to monitor parameters such as temperature, humidity and electromagnetic interference in the test environment in real time, and uses these environmental parameters as input to the adaptive filtering algorithm of the noise filtering unit to further improve the noise filtering effect and system adaptability.

[0106] Through this embodiment, the data processing module realizes noise filtering and signal enhancement based on the adaptive filtering algorithm, effectively improving the data accuracy and anti-interference ability of the PTC heater test system. High-quality signal processing not only improves the reliability of the test results, but also provides a solid data foundation for subsequent performance analysis and evaluation.

[0107] The benefit of this embodiment is that by introducing advanced noise filtering and signal enhancement technology, the data processing capability of the PTC heater test system is significantly improved, ensuring high accuracy and high reliability of the test data. Through the optimized design of this embodiment, the PTC heater test system can more accurately evaluate the performance of the heater.

[0108] Embodiment 5

[0109] refer to Figures 1 to 5As shown, in order to solve the problem of accurately evaluating the energy conversion efficiency of the PTC heater during the test, this embodiment further optimizes the energy conversion module 7, and especially introduces an energy balance calculation unit. The calculation unit monitors the power input and heat output of the PTC heater in real time and uses the energy balance formula to evaluate the heating efficiency and energy loss.

[0110] According to the data processing module described in the above embodiment, this embodiment integrates an energy balance calculation unit in the energy conversion module 7. The unit uses a high-precision sensor and a data acquisition system to monitor the power input and temperature change of the PTC heater in real time. Specifically, the energy balance calculation unit measures the instantaneous power P(t) of the heater through a high-precision power meter, model Yokogawa WT5000. The power meter has the characteristics of high-frequency response and high precision, and can accurately capture the dynamic changes of power input.

[0111] Furthermore, in terms of temperature measurement, the energy balance calculation unit uses a high-speed response thermocouple, model OMEGA K-type thermocouple, to monitor the temperature changes on the surface and inside of the heater in real time. The thermocouple has high sensitivity and a wide measurement range, and can accurately capture the rate of change of temperature over time dT / dt. In order to improve the stability of temperature data, the thermocouple is connected to a high-precision temperature data acquisition system, model NI 9213, to ensure real-time and accurate acquisition of temperature data.

[0112] Furthermore, the energy balance calculation unit processes and analyzes the real-time collected power and temperature data through an integrated data processing algorithm. According to the energy conversion formula:

[0113]

[0114] Where η represents the energy conversion efficiency, m represents the mass of the heater, c represents the specific heat capacity of the heater material, dT / dt represents the rate of change of temperature over time, and P(t) represents the power that changes over time. The calculation unit integrates the collected time series data through a numerical integration method to obtain the energy conversion efficiency η.

[0115] It is important to understand that the energy balance calculation unit is not limited to calculating the energy conversion efficiency, but can also evaluate the energy loss and thermal efficiency of the system by analyzing the difference between power input and heat output. Through real-time monitoring and analysis, the performance of the heater under different operating conditions is fully evaluated. For example, by comparing the energy conversion efficiency at different time periods, the energy loss of the heater during startup, stable operation and shutdown can be identified.

[0116] Furthermore, in order to improve the calculation efficiency of the energy balance calculation unit, a high-performance computing platform, model NVIDIA Jetson Xavier, is used in this embodiment. The platform has powerful parallel computing capabilities and can process large amounts of data in real time and perform complex calculations. With the support of the high-performance computing platform, the energy balance calculation unit can complete the processing and analysis of large amounts of data in an instant, ensuring real-time calculation of energy conversion efficiency.

[0117] In addition, this embodiment also combines an environmental monitoring unit to monitor parameters such as temperature, humidity and airflow in the test environment. These environmental parameters are used as auxiliary data input for energy balance calculation, further improving the accuracy of energy conversion efficiency calculation. For example, in a high humidity environment, the factors affecting heat loss are different, and environmental monitoring data can help adjust the calculation model, increase or decrease compensation, to improve the accuracy of the evaluation.

[0118] Through the design of this embodiment, the energy conversion module 7 realizes real-time calculation and monitoring based on the energy balance formula, and effectively evaluates the heating efficiency and energy loss of the PTC heater. The high precision and real-time performance of the energy balance calculation unit enable the test system to accurately measure and analyze the performance of the heater under dynamic conditions, providing reliable data support for the optimal design and performance improvement of the heater.

[0119] Through this embodiment, the PTC heater testing system has made significant progress in the evaluation of energy conversion efficiency, which not only improves the test accuracy, but also enhances the real-time monitoring capability of the system, providing a solid technical foundation for further research and application.

[0120] Embodiment 6

[0121] refer to Figures 1 to 3 As shown, according to the energy balance calculation unit described in the above embodiments, this embodiment further optimizes the controller 4 by introducing an environmental compensation module to dynamically adjust the performance parameters of the PTC heater to ensure the accuracy of the test results.

[0122] In order to solve the problem of the influence of the change of the performance parameters of the PTC heater under different environmental conditions on the test results, this embodiment further optimizes the design of the controller 4, and especially adds an environmental compensation module. The environmental compensation module dynamically compensates the measurement data based on the preset environmental impact model by real-time detection of environmental temperature, humidity, air pressure and other parameters to ensure the accuracy and consistency of the test results.

[0123] The environmental compensation module uses a variety of high-precision sensors to detect ambient temperature, humidity and air pressure. The ambient temperature sensor 1 uses the HONEYWELL 1920 series, which has high precision and fast response characteristics and can monitor ambient temperature changes in real time. The humidity sensor uses the Sensirion SHT3x series, which has high sensitivity and a wide measurement range and can accurately detect ambient humidity. The pressure sensor uses the Bosch BMP388, which has high resolution and high stability and can accurately measure ambient pressure changes.

[0124] Furthermore, the environmental compensation module performs temperature compensation based on the following formula using the detected environmental parameters:

[0125] Tc = Tm-k·(Te-Tm);

[0126] Among them, Tc represents the compensated temperature, Tm represents the measured temperature, Te represents the ambient temperature, and k represents the compensation coefficient. This formula introduces the compensation coefficient k to correct the measured temperature according to the difference between the ambient temperature and the measured temperature, thereby reducing the impact of environmental conditions on the test results.

[0127] It should be understood that the compensation coefficient k is not a fixed value, but is dynamically adjusted according to the preset environmental impact model. Specifically, the environmental compensation module analyzes the combined impact of ambient temperature, humidity and air pressure on the performance of the PTC heater, and uses multivariate regression analysis and machine learning algorithms to dynamically adjust the compensation coefficient k to adapt to the compensation needs under different environmental conditions. For example, in a high humidity and low pressure environment, the compensation coefficient k may need to be increased to effectively compensate for the impact of environmental conditions on the heater performance.

[0128] Furthermore, the environmental compensation module is not limited to temperature compensation, but also includes compensation for humidity and air pressure. Through multi-sensor data fusion technology, the environmental compensation module can comprehensively analyze the changes in environmental parameters and perform multi-dimensional compensation for the performance parameters of the PTC heater. For example, in an environment with high humidity, the impact of humidity on heating efficiency may be more significant. The environmental compensation module can adjust the compensation coefficient based on humidity data to improve the accuracy of the test data.

[0129] Furthermore, this embodiment also considers the collaborative work between the environmental compensation module and the energy balance calculation unit. The environmental compensation module outputs the compensated temperature data in real time for the energy balance calculation unit to calculate the energy conversion efficiency. Through efficient data interaction and processing, the entire system can maintain high-precision energy conversion efficiency evaluation under complex environmental conditions and ensure the reliability of the test results.

[0130] It is important to understand that the introduction of the environmental compensation module not only improves the accuracy of the test system, but also enhances the system's adaptability to different environmental conditions. For example, in extreme temperature or high humidity environments, the environmental compensation module can effectively correct the measurement data to ensure that the performance evaluation of the PTC heater is not significantly affected by environmental factors.

[0131] Through the design of this embodiment, the controller 4 realizes dynamic compensation based on environmental conditions, improving the accuracy and adaptability of the PTC heater test system. The efficient operation of the environmental compensation module enables the test system to always maintain accurate and reliable test results under changing environmental conditions, providing solid data support for the performance optimization and research and development of the heater.

[0132] The benefit of this embodiment is that, by introducing the environmental compensation module, the problem of the influence of environmental conditions on the test results is effectively solved, ensuring the high accuracy and high reliability of the PTC heater test system. Through the optimized design of this embodiment, the test system can perform reliable performance evaluation under a wider range of environmental conditions, providing practical technical guarantees for the testing, development and improvement of heaters.

[0133] Embodiment 7

[0134] refer to Figure 6 As shown, according to the PTC heater testing system described in the foregoing embodiments, this embodiment provides a method for testing a PTC heater using the system to ensure a comprehensive evaluation and accurate testing of the performance of the PTC heater.

[0135] Furthermore, in order to solve the performance parameter measurement and accuracy issues of the PTC heater during the test, this embodiment further refines the test steps, covering the entire process from device connection, data collection to result display and fault diagnosis.

[0136] In the specific implementation process, the PTC heater to be tested is first connected to the test system. The test system includes temperature sensor 1, current sensor 2 and voltage sensor 3, which are used to detect the surface temperature, ambient temperature, current and voltage of the PTC heater respectively. Temperature sensor 1 uses OMEGA K-type thermocouple, which has high response speed and accuracy and can monitor the temperature change of the heater in real time. Current sensor 2 and voltage sensor 3 use LEM HXS series and Fluke8846A digital multimeter respectively to ensure the accuracy of current and voltage measurement.

[0137] Further, after the PTC heater is started, the temperature sensor 1 starts to detect its surface temperature and ambient temperature, and the current sensor 2 and the voltage sensor 3 detect the current and voltage of the PTC heater respectively. At this time, the controller 4 receives and processes the data from each sensor. The controller 4 uses the NVIDIA Jetson Xavier high-performance computing platform, and uses its powerful computing power and data processing capabilities to process the collected data in real time.

[0138] It should be understood that the controller 4 is not limited to simple data reception and processing, but also calculates the performance parameters of the PTC heater, including heat output and energy conversion efficiency, through the energy balance calculation unit. The controller 4 accurately calculates the energy conversion efficiency of the heater through a high-precision integration method.

[0139] Furthermore, the controller 4 stores the calculated performance parameters in the data storage device 5. The preferred storage device is Samsung 970EVO Plus NVMe SSD, which has high-speed reading and writing capabilities to ensure the timeliness and security of data storage. At the same time, the calculation results are displayed in real time on the display 6. The display 6 adopts Dell UltraSharp U2719D, which has high resolution and wide viewing angle, so that the operator can intuitively view the test results.

[0140] Furthermore, in order to ensure the accuracy of the test results, the environmental compensation module performs dynamic compensation according to the external environmental conditions. The compensation coefficient k is dynamically adjusted through a preset environmental impact model. The specific model uses multivariate regression analysis and machine learning algorithms to ensure the accuracy and real-time performance of the compensation.

[0141] Another important step of this embodiment is to run the fault diagnosis module 9 to detect and diagnose the fault state of the PTC heater. The fault diagnosis module 9 uses big data analysis and artificial intelligence algorithms based on sensor data and historical data to identify the failure mode and potential problems of the heater. This module uses the IBM Watson platform for fault diagnosis, has powerful data analysis and machine learning capabilities, and can quickly and accurately detect the fault state of the heater.

[0142] It should be understood that the fault diagnosis module 9 can not only detect the current fault of the heater, but also, through the predictive maintenance algorithm, give early warning of possible faults and provide maintenance suggestions, thereby extending the service life of the heater and improving the reliability of the system.

[0143] The benefit of this embodiment is that the performance of the PTC heater can be comprehensively evaluated through a systematic and refined testing method. In addition, the PTC heater testing method not only covers the various components of the testing system and the data processing steps, but also ensures the accuracy and reliability of the test results through functions such as environmental compensation and fault diagnosis.

[0144] Embodiment 8

[0145] refer to Figure 6 and Figure 7 As shown, according to the PTC heater testing method described in the above embodiments, this embodiment further refines the sensor calibration step before starting the PTC heater to ensure the accuracy and reliability of data measurement.

[0146] In order to solve the problem of deviation and error that may occur in the long-term use of the sensor, this embodiment optimizes the sensor calibration process by pre-calibrating before the test starts to ensure that the data of each test is accurate. The specific implementation steps are as follows:

[0147] Before starting the PTC heater, the sensor is calibrated first. This step includes the calibration of voltage sensor 3 and current sensor 2. The calibration equipment selected for voltage sensor 3 is Fluke 5522A multifunction calibrator, which has high precision and stability and can accurately calibrate voltage sensor 3. The calibration equipment for current sensor 2 is Yokogawa WT500 power analyzer to ensure the accuracy of current measurement.

[0148] The calibration process is performed using the following formula:

[0149] V cal =V meas +ΔV,I cal =I meas +ΔI;

[0150] Among them, Vcal and Ical represent the calibrated voltage and current respectively, Vmeas and Imeas represent the measured voltage and current respectively, and ΔV and ΔI represent the calibration values. ΔV and ΔI are obtained through preset calibration standards and equipment and applied to the calibration of measured data to ensure the accuracy of the data.

[0151] Furthermore, the calibration process needs to ensure that the sensor is carried out under stable environmental conditions. The stability of environmental conditions is controlled by using a constant temperature and humidity chamber. The equipment uses an ESPEC constant temperature and humidity chamber to ensure that the ambient temperature and humidity are constant during the calibration period, avoiding the influence of environmental changes on the calibration results.

[0152] It is important to understand that the calibration step is not only performed before the test, but can also be performed regularly during the test to address sensor drift and error accumulation problems caused by long-term testing. The controller 4 has a built-in automatic calibration program that automatically triggers the calibration process at regular intervals to ensure the continued accuracy of the sensor data.

[0153] Further, after completing the sensor calibration, the PTC heater is started according to the aforementioned steps, and data is collected through the temperature sensor 1, the current sensor 2, and the voltage sensor 3. The controller 4 receives and processes the data from the sensors and calculates the performance parameters of the PTC heater, including heat output and energy conversion efficiency. The calibrated sensor data improves the accuracy and reliability of the calculation results.

[0154] Furthermore, the controller 4 performs compensation according to the external environmental conditions to ensure the accuracy of the test results. The environmental compensation module dynamically adjusts the compensation coefficient k and corrects the measurement data based on the real-time monitored ambient temperature, humidity and air pressure data. The specific compensation process refers to the above formula, where k is dynamically adjusted according to the environmental impact model to ensure the accuracy of the compensation.

[0155] In addition, in this embodiment, the fault diagnosis module 9 monitors the sensor data in real time during the test process, and identifies the fault state of the PTC heater through big data analysis and artificial intelligence algorithms. The module performs fault pattern recognition based on the real-time data and historical data of the sensor, provides real-time fault warnings and maintenance suggestions, and uses the fault diagnosis system of the IBM Watson platform to achieve fast and accurate fault detection.

[0156] It is understandable that the fault diagnosis module 9 can not only detect the current fault, but also provide early warning of possible faults through predictive maintenance algorithms and provide maintenance suggestions, thereby extending the service life of the heater and improving the reliability of the system.

[0157] The benefit of this embodiment is that the PTC heater test method covers the entire process from sensor calibration, data acquisition, performance calculation to environmental compensation and fault diagnosis. The introduction and optimization of the calibration steps ensure the accuracy of data measurement and the reliability of test results. Through a systematic and refined test method, the performance of the PTC heater is comprehensively evaluated, providing solid technical support for the optimal design and application of the heater. Through the optimized design of this embodiment, the test system can perform reliable performance evaluation under a wider range of environmental conditions.

[0158] Embodiment 9

[0159] refer to Figure 6 and Figure 7As shown, according to the PTC heater testing method described in the foregoing embodiments, this embodiment further refines the steps of sensor data processing and data transmission to improve data accuracy and availability of test results.

[0160] In order to solve the noise problem in the sensor data, this embodiment optimizes the data processing process and processes the sensor data through a filtering algorithm to remove noise and improve the accuracy and reliability of the data. In the specific implementation process, after receiving the data from the sensor, the controller 4 first filters the data. The filtering algorithm includes but is not limited to adaptive filtering and fast Fourier transform FFT.

[0161] Furthermore, the adaptive filter uses the LMS Last Mean Squares algorithm, which can dynamically adjust the filter parameters according to the characteristics of the input signal and effectively remove noise. In the specific implementation, the controller 4 adjusts the filter coefficient in real time based on the LMS algorithm to ensure that the best filtering effect can be obtained under different noise environments. Fast Fourier transform FFT is used for frequency domain analysis, which identifies and removes high-frequency noise components by converting time domain signals into frequency domain signals. After FFT processing, the controller 4 performs an inverse transform I FFT on the frequency domain signal, restores it to the time domain signal, and obtains the denoised sensor data.

[0162] It should be understood that filtering not only improves the accuracy of the data, but also provides more accurate basic data for subsequent performance parameter calculations. After filtering, the controller 4 uses the denoised data to calculate performance parameters such as the heat output and energy conversion efficiency of the PTC heater.

[0163] Furthermore, after the test is completed, the controller 4 sends all test data and calculated performance parameters to an external device or cloud server through the communication module for further analysis and storage. The communication module uses high-speed wireless communication technology and selects 5G NRNew Radio module to ensure the efficiency and stability of data transmission. During data transmission, the AES-256 encryption algorithm is used to ensure the security and integrity of the data.

[0164] Furthermore, after the data is transmitted to an external device or cloud server, the server uses a big data analysis platform to conduct in-depth analysis and mining of the collected data. The analysis platform is based on the Hadoop and Spark technology framework, which can process massive amounts of data and perform real-time analysis. Through data mining algorithms, the performance trends and potential problems of PTC heaters can be identified, providing strong support for the optimal design of heaters.

[0165] Furthermore, the server side also has data visualization capabilities, using data visualization tools such as Tableau or Power BI to display the analysis results in the form of charts and reports, making it convenient for technicians and managers to intuitively understand the test results and performance parameters.

[0166] It should be understood that the data processing and transmission steps in this embodiment not only improve the accuracy and transmission efficiency of the data, but also provide high-quality data support for subsequent analysis and decision-making. The noise is removed by the filtering algorithm to ensure the accuracy of the sensor data; the stability and security of data transmission are ensured by the high-speed communication module and encryption algorithm; the in-depth analysis of the data and the display of the results are realized by the big data analysis platform and visualization tools.

[0167] Through this embodiment, the PTC heater test method is fully optimized in terms of data processing and transmission, ensuring the accuracy of test data and the efficiency of transmission. Through a systematic and refined data processing and transmission method, the reliability and availability of the PTC heater test are comprehensively improved.

[0168] Embodiment 10

[0169] According to the PTC heater testing system and testing method described in the above embodiments, this embodiment provides a readable medium having a computer program stored thereon, which implements the various steps and functions of the above PTC heater testing method when executed by a processor.

[0170] In order to solve the problems of inaccurate data and inconvenient testing caused by human factors or hardware limitations, this embodiment further optimizes the automation and intelligence of the PTC heater testing method. The readable medium can be a non-volatile storage medium, such as a solid state drive SSD, flash memory or CD / DVD, etc., on which a complete set of computer programs is stored. The computer program includes multiple functional modules, each of which implements different steps and functions of the PTC heater testing method.

[0171] Specifically, in this embodiment, the computer program includes the following main functional modules:

[0172] The sensor calibration module contains the sensor calibration algorithm and parameters. During initialization, the preset calibration standard is called to calibrate the sensor. The calibration parameters are automatically generated by the difference between the preset standard value and the current measurement value to ensure the data accuracy of the voltage and current sensor 2. For example, by calling the Fluke 5522A multi-function calibrator interface, the calibration process of the voltage sensor 3 is completed.

[0173] Data acquisition and filtering module, which is responsible for real-time acquisition of voltage, current and temperature data of PTC heaters, and filtering the acquired data to remove noise. The filtering algorithm includes adaptive filtering and fast Fourier transform (FFT) algorithm. LMS adaptive filter and FFT are used to process noise in different frequency bands, greatly improving data accuracy.

[0174] Performance calculation module, after the sensor data is filtered, this module calculates the heat output and energy conversion efficiency of the heater. The calculation method is based on the real-time collected voltage, current and temperature data, combined with the characteristics of the PTC material and the heat conduction model, making the calculation results more accurate.

[0175] Data transmission and storage module, which is responsible for sending test data and calculation results to external devices or cloud servers through high-speed wireless communication modules. The communication module uses 5G NR technology to ensure rapid and stable data transmission. At the same time, the module performs AES-256 encryption before transmitting data to ensure data security.

[0176] Real-time monitoring and fault diagnosis module 9: This module monitors real-time sensor data and uses big data analysis and artificial intelligence algorithms to identify fault patterns. The fault diagnosis system of the IBM Watson platform is implemented in this module, providing real-time fault warnings and maintenance suggestions to ensure the stability and reliability of the system.

[0177] User interface and visualization module, which provides users with a friendly interface and uses data visualization tools such as Tableau or PowerBI to intuitively display test data and analysis results. Users can view the performance parameters and test results of PTC heaters in the form of charts and reports for further analysis and decision-making.

[0178] Furthermore, to ensure efficient operation of computer programs, the program architecture and logical connections are optimized. Multithreading technology and asynchronous programming technology are adopted to improve the execution efficiency and response speed of the program. When necessary, the program can call the GPU-based parallel computing function to accelerate the execution of complex computing tasks.

[0179] It should be understood that there is a close logical connection between the modules in the computer program. The sensor calibration module ensures the accuracy of the basic data, while the data acquisition and filtering module further improves the accuracy of the data, which provides reliable input for the performance calculation module. The data transmission and storage module ensures the timeliness and security of the test results, while the real-time monitoring and fault diagnosis module 9 provides the system's adaptive capabilities and maintenance suggestions through intelligent analysis. The user interface and visualization module displays the results of the entire process in an intuitive form, improving the user experience and operational convenience.

[0180] Through the computer program of this embodiment, the PTC heater testing method is fully automated and intelligent, and can be completed efficiently and accurately from sensor calibration, data acquisition and filtering, performance calculation, data transmission and storage to real-time monitoring and fault diagnosis. It not only improves the accuracy and reliability of the testing method, but also significantly improves the convenience of operation and the intelligence level of the system, so that the PTC heater testing method of the present invention can operate stably in various complex environments, meet various application requirements, and further promote the advancement and application of PTC heater technology.

[0181] The beneficial effects of the present invention are specifically embodied in that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A PTC heater testing system, characterized in that: The test system comprises: A temperature sensor, used to detect the surface temperature and ambient temperature of the PTC heater; A current sensor and a voltage sensor, used to detect the current and voltage passing through the PTC heater; a controller connected to the temperature sensor, the current sensor and the voltage sensor, and calculating the performance parameters and test data of the PTC heater based on the detected temperature, current and voltage data; a data storage device, connected to the controller, for storing the performance parameters and test data; A display, connected to the controller, for displaying the performance parameters and test data; an energy conversion module for calculating heat output and energy conversion efficiency based on electrical input of the PTC heater; An environmental monitoring module, used to detect the influence of external environmental conditions on the performance of the PTC heater; A fault diagnosis module, used for detecting and diagnosing a fault state of the PTC heater; The energy conversion module includes an energy balance calculation unit, which calculates the energy conversion efficiency using the following formula: Wherein, η represents the energy conversion efficiency, m represents the mass of the heater, c represents the specific heat capacity of the PTC heater material, dT / dt represents the rate of change of temperature over time, and P(t) represents the power that changes over time; The energy balance calculation unit evaluates heating efficiency and energy loss by monitoring the power input and heat output of the PTC heater in real time; The controller further includes an environmental compensation module for dynamically adjusting the performance parameters of the PTC heater based on changes in external environmental conditions to ensure the accuracy of the test results; The environmental compensation module detects the ambient temperature, humidity and air pressure parameters and performs compensation based on the following formula: Tc = Tm-k·(Te-Tm); Wherein, Tc represents the compensated temperature, Tm represents the measured temperature, Te represents the ambient temperature, and k represents the compensation coefficient; Based on the temperature, humidity and air pressure of the test environment, the compensation coefficient k is dynamically adjusted according to a preset environmental impact model.

2. The PTC heater testing system according to claim 1, characterized in that: The controller includes a data processing module and an analysis module. The data processing module is used to process the raw data from the sensor. The analysis module is used to analyze the processed data to obtain the performance parameters and test data. The analysis module calculates the heat output based on the following formula: Where Q represents the heat output, P(t) represents the power that varies with time, V(t) represents the voltage that varies with time, I(t) represents the current that varies with time, and t represents time.

3. The PTC heater testing system according to claim 2, characterized in that: The data processing module includes a high-frequency sampling unit, which collects voltage data and current data of the PTC heater at a high sampling rate and performs frequency domain analysis on the voltage data and current data through fast Fourier transform.

4. The PTC heater testing system according to claim 3, characterized in that: The data processing module also includes a noise filtering unit and a signal enhancement unit, which process the data in real time based on an adaptive filtering algorithm to remove environmental noise and signal interference.

5. A PTC heater testing method, using the PTC heater testing system according to any one of claims 1 to 4, characterized in that: The test method comprises the following steps: Connect the PTC heater to the test system; Start the PTC heater and detect its surface temperature and ambient temperature through the temperature sensor; Detect the current and voltage of the PTC heater through a current sensor and a voltage sensor; The controller receives and processes data from the sensor and calculates the performance parameters of the PTC heater, including heat output and energy conversion efficiency; storing the calculated performance parameters in a data storage device and displaying them on a display; Compensate based on external environmental conditions to ensure the accuracy of test results; Run the fault diagnosis module to detect and diagnose the fault status of the PTC heater.

6. The PTC heater testing method according to claim 5, characterized in that: The test method further comprises the following steps: Before starting the PTC heater, calibrate the sensor in advance to ensure the accuracy of the data. Calibrate using the following formula: V cal =V meas +ΔV,I cal =I meas +ΔI; Wherein, Vcal and Ical represent the calibrated voltage and current respectively, Vmeas and Imeas represent the measured voltage and current respectively, and ΔV and ΔI represent the calibration values.

7. The PTC heater testing method according to claim 6, characterized in that: The test method further comprises the following steps: Processing sensor data through filtering algorithms to remove noise and improve data accuracy, the filtering algorithms include but are not limited to adaptive filtering and fast Fourier transform; After the test is completed, the test data and performance parameters are sent to external devices or cloud servers through the communication module for further analysis and storage.

8. A readable medium, characterized in that A computer program is stored thereon, and when the computer program is executed by a processor, the computer program implements the PTC heater testing method according to any one of claims 5 to 7.

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