Calibration system and method for commercial vehicle air conditioning system based on multi-sensor and multi-actuator

Abstract

A calibration system and method for a commercial vehicle air conditioning system based on a multi-sensor multi-actuator, the calibration system includes a calibration sensor system, which is mainly composed of multi-channel temperature sensors arranged inside the cockpit and on the vehicle body, and is used to collect temperature data of multiple air outlets in the cockpit, the driver / co-pilot side, and the entire vehicle; a data acquisition and calibration system, including a temperature sensor acquisition tool and a calibration system, the temperature sensor acquisition tool is connected to the calibration sensor system and the air conditioning controller, and the resistance signal of each temperature sensor is converted into a temperature signal after processing and sent to the air conditioning controller, and the calibration system is connected to the air conditioning controller to modify the data inside it; a data analysis system, including a MATLAB data analysis toolbox associated with the data acquisition and calibration system, is used to find the optimal control point. The present invention can adopt different control strategies according to different working conditions, ensure that the air conditioning system can adapt to various working conditions, and ultimately improve comfort.

Description

Technical Field

[0001] The present invention relates to a commercial vehicle air-conditioning calibration system and method, in particular to a calibration system and method based on a multi-sensor multi-actuator commercial vehicle air-conditioning system, belonging to the technical field of commercial vehicle air-conditioning calibration. Background Art

[0002] At present, it is well known that in recent years, with the continuous development of automobile technology, the role of automobile air conditioning has become more and more important. People have gradually increased their requirements for the stability, power and safety of automobiles, and their requirements for comfort have also become higher and higher. Automobiles are not only a means of transportation, but also a mobile living place, which needs to provide customers with a more comfortable driving environment.

[0003] Especially for commercial vehicles, which are used to transport people and goods in terms of design and technical characteristics, they are usually divided into two categories: passenger cars and trucks. Drivers of these vehicles often drive for long periods of time due to work needs, so their air conditioning systems are required to have good comfort, which can greatly reduce the driver's fatigue and improve driving safety.

[0004] In order to improve the comfort of commercial vehicle air conditioning systems, it is necessary to perform special calibration on the air conditioning systems. However, the existing calibration systems and methods for commercial vehicle air conditioning systems have the following deficiencies or disadvantages:

[0005] 1) Simply setting a temperature sensor at the air outlet cannot reflect the situation inside the cockpit. Since the cockpit has a complex structure and multiple air outlets, the temperatures of different air outlets are different, and the temperature from the air outlet to the driver is also different. The sensor arrangement method used in the existing calibration method affects the accuracy of the calibration result;

[0006] 2) The calibration environment is too simple and cannot be applied to different working conditions. The existing calibration methods are generally tested in the ring mold laboratory or in the external environment, and are not calibrated in some special extreme working conditions, which cannot improve the comfort under all working conditions;

[0007] 3) The calibration method can only be applied to specific systems. It is not possible to use the same calibration system for different platforms. For example, different calibration methods are required for electric systems and fuel systems, making it difficult to ensure consistency. Summary of the invention

[0008] In order to overcome the above-mentioned deficiencies in the prior art, the present invention provides a calibration system and method for a commercial vehicle air-conditioning system based on a multi-sensor and multi-actuator, which can collect data of the air-conditioning system under different working conditions and optimize the control strategy to ensure that the air-conditioning system can adapt to various working conditions and adopt different control strategies according to different working conditions, thereby ultimately improving comfort.

[0009] The technical solution adopted by the present invention to solve the technical problem is:

[0010] A calibration system based on a multi-sensor multi-actuator commercial vehicle air-conditioning system comprises a calibration sensor system, which is mainly composed of multiple temperature sensors arranged inside a cockpit and on a vehicle body, and is used to collect temperature data of multiple air outlets in the cockpit, driver / co-pilot sides and the entire vehicle; a data acquisition and calibration system, which comprises a temperature sensor acquisition tool and a calibration system, wherein the temperature sensor acquisition tool is connected to the calibration sensor system and an air-conditioning controller, and converts resistance signals of each temperature sensor into temperature signals after processing and sends them to the air-conditioning controller, and the calibration system is connected to the air-conditioning controller, and modifies the data inside the air-conditioning controller and allows the air-conditioning controller to upload the collected data in real time; and a data analysis system, which comprises a MATLAB data analysis toolbox associated with the data acquisition and calibration system, and is used to integrate, analyze, automatically fit and optimize the collected data to find the optimal control point.

[0011] Furthermore, the commercial vehicle air-conditioning system includes a compressor, a blower, an internal and external circulation damper, a cold and warm mixing damper, a mode damper, a condensing fan, an in-vehicle temperature sensor, an outside temperature sensor, an evaporating temperature sensor and an air-conditioning controller. The air-conditioning controller has a calibration interface associated with a calibration system for modifying control variables inside the controller and obtaining data collected by the controller in real time; the in-vehicle temperature sensor, the outside temperature sensor and the evaporating temperature sensor are respectively connected to a temperature sensor acquisition tool of the data acquisition and calibration system.

[0012] Preferably, the multi-channel temperature sensors are all thermocouple temperature sensors, which are respectively arranged at the left face air outlet, the middle face air outlet, the right face air outlet, the left foot air outlet, the right foot air outlet, the left window air outlet, the right window air outlet, the middle window air outlet, the driver's head position, the co-pilot's head position, the middle position of the cockpit, the berth position, the water inlet and outlet pipes, the fuel tank and the front cover of the vehicle, and are all connected to the temperature sensor collection tool of the data acquisition and calibration system.

[0013] Furthermore, the calibration system includes a calibration tool and a calibration protocol, and is based on a CAN field bus, and performs data collection and calibration through the calibration protocol and the calibration tool.

[0014] Preferably, the calibration protocol is CCP / XCP; the calibration tool is CANape or VehSpy.

[0015] A calibration method for a commercial vehicle air conditioning system calibration system based on a multi-sensor multi-actuator system comprises the following steps:

[0016] 1) Screening control variables: First, find all the control variables of the commercial vehicle air conditioning system, then list the range of the control variables and find the limit value, modify each variable to the limit value, test it, and then analyze its impact on the test results, and find the N control variables with the largest impact;

[0017] 2) Test the control variables in sections: Plot the N control variables into N*N tables, where only one row in each table changes equally within the range, and the other values ​​remain unchanged. Then modify the control variables according to the table, and then record the test data and results for each time;

[0018] 3) Statistical analysis of test results: The test results are unified and integrated, and multiple groups of maps are calculated using algorithms such as interpolation, and then interpolation is performed again to calculate multiple points and integrate them into the control algorithm;

[0019] 4) Optimize test: Optimize and delete test steps based on analysis results, remove redundant test items, and analyze the matching relationship between working conditions and data.

[0020] Preferably, the control variables and their ranges in step 1) include the PWM range of the blower of 0 to 100, the control range of the compressor of 0 to 1, the control range of the heating and cooling air doors of 0 to 100, the control range of the internal and external circulation air doors of 0 to 1, and the control range of the mode air door of 1 to 5.

[0021] Preferably, the testing process in step 1) includes: using the MATLAB data analysis toolbox to import the collected data, and transforming the data according to the file format, interpolating according to time, and unifying the time coordinate axis; then calculating the impact amplitude according to the formula, and using the Curve toolbox to automatically fit the curve, analyzing the relationship between the control variables, screening outliers, and fitting to a new formula, and using the optimal control algorithm to find the optimal control point.

[0022] Preferably, the formula for calculating the impact amplitude is to subtract the corresponding offset from the collected value collected by each sensor, and then multiply it by various weights and add them up; the larger the value calculated by this formula, the greater the impact factor, and the more important the control variable is to the result.

[0023] Preferably, the step 3) specifically includes: sorting and analyzing the final test results, fitting the final Map table, smoothing the surface using cubic spline interpolation, and then performing N-dimensional interpolation calculation according to the dimension of the control table, and then performing inverse operation, reversely solving the control variables according to the calculation results, decoupling each control variable, and obtaining the relationship between the result and the control variable; changing the Map into a control algorithm and integrating it into the controller; when using it, reversely solving the control value according to the set value, and then calculating the deviation in real time according to the feedback value, and correcting and filtering the control variable.

[0024] Compared with the prior art, the calibration system and method of the commercial vehicle air conditioning system based on multi-sensor multi-actuator of the present invention can be tested under various working conditions by arranging multiple sensors inside the cockpit and on the body during calibration, and collect information such as temperature and humidity of the whole vehicle in real time, and fit, compare and analyze the sensor data of the commercial vehicle air conditioning system, and modify the control strategy according to the control variable method, analyze the impact of changing the control amount on comfort, and find the optimal solution. Finally, according to the fitting data, the sensors of the commercial vehicle air conditioning system are reduced, and the environment in the cockpit is fitted and calculated through the existing sensors, so that the control strategy can meet the use under different working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0026] Figure 1 It is a structural block diagram of a calibration system according to an embodiment of the present invention.

[0027] Figure 2 It is a schematic diagram of the arrangement of multiple temperature sensors in one embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. 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.

[0029] Figure 1 and Figure 2 A structural schematic diagram of a preferred embodiment of the present invention is shown, in which the calibration system based on a multi-sensor and multi-actuator commercial vehicle air-conditioning system is mainly composed of a commercial vehicle air-conditioning system, a calibration sensor system, a data acquisition and calibration system, and a data analysis system.

[0030] Among them, the commercial vehicle air conditioning system includes a compressor, a blower, an internal and external circulation damper, a cold and warm mixing damper, a mode damper, a condensing fan, an in-vehicle temperature sensor, an outside temperature sensor, an evaporation temperature sensor, an air conditioning controller, etc. The commercial vehicle air conditioning system is used to control the cooling, heating, ventilation, etc. of the entire vehicle, and to control and adjust the temperature and humidity in the cockpit. The compressor is used to control refrigeration, collect the current refrigeration effect through the evaporation temperature sensor, and protect the evaporator. The blower is used to adjust the wind speed. Various dampers are used to mix gases of different temperatures and humidities, or to adjust the blowing angle. The in-vehicle and outside temperature sensors are used to determine the current working conditions and adjust the control strategy. The air conditioning controller needs to have a calibration interface, which can modify the control variables inside the controller through the calibration system, and can obtain the data collected by the controller in real time.

[0031] The calibration sensor system includes multiple temperature sensors, which are mainly used to collect temperature data from multiple air outlets in the cockpit, as well as data from the driver and co-pilot sides, and the temperature data of the entire vehicle. The temperature sensor uses thermocouples, which are arranged at the left air outlet, middle air outlet, right air outlet, left foot air outlet, right foot air outlet, left window air outlet, right window air outlet, middle window air outlet, driver's head position, co-pilot's head position, middle position of the cockpit, berth position, water inlet and outlet pipes, fuel tank, front cover and other positions, and uses temperature sensor acquisition tools to collect temperature in real time.

[0032] The data acquisition and calibration system mainly includes the temperature sensor acquisition system and the calibration system. The temperature sensor acquisition tool mainly converts the resistance signal of each temperature sensor into a temperature signal after processing, calculates the current temperature according to the resistance of the thermocouple, and sends it to the air-conditioning controller for real-time acquisition and display. The calibration system mainly modifies the data inside the air-conditioning controller through the calibration interface, and allows the air-conditioning controller to upload the collected data in real time. The calibration system mainly uses the CAN field bus to modify or read the data inside the controller through calibration protocols such as CCP and XCP, and uses highly reliable calibration tools such as CANape and VehSpy for acquisition and calibration. The calibration system collects and analyzes data under different working conditions. Under each working condition, multiple rounds of different tests are required. According to the number of control variables, multiple tables are made to record the test results, and the results are processed according to the algorithm. Then, the variables are modified and retested, and the changing trend of the test results is analyzed to find the optimal solution.

[0033] The data analysis system is mainly used to integrate and analyze the collected data, organize it into easy-to-parse data, and automatically fit and optimize the collected data to find the optimal control point. The data analysis system is mainly developed using Matlab, using its own toolbox and development tools (i.e., MATLAB data analysis toolbox) to automatically and manually analyze the data, improve the analysis speed and accuracy, reduce the complexity of manual processing, and increase the calibration speed.

[0034] The specific steps of the calibration method in the embodiment of the present invention are as follows:

[0035] 1. Arrange multiple temperature sensors at various positions in the cockpit, including left window blowing sensor, right window blowing sensor, middle window blowing sensor, left blowing surface sensor, right blowing surface sensor, middle blowing surface sensor, left blowing foot sensor, right blowing foot sensor, main driving sensor, co-pilot sensor, cockpit sensor, berth sensor, environmental sensor, fuel tank sensor, water tank sensor, etc. Use tape and other tools to fix them to ensure good ventilation during collection, stable contact with the heat source, and not blocked by other things.

[0036] 2. Classify and number each sensor according to its position. For example, the face-blowing sensors are grouped into one group, the window-blowing sensors are grouped into one group, and the foot-blowing sensors are grouped into one group. Then use the temperature sensor acquisition tool to observe the temperature distribution and confirm that the values ​​collected by the temperature sensor are accurate and the change pattern is consistent with the actual value.

[0037] 3. According to the controllable equipment, count all control variables and control ranges. For example, the PWM range of the blower is 0-100, the control range of the compressor is 0-1, the control range of the heating and cooling air door is 0-100, the control range of the internal and external circulation air door is 0-1, and the control range of the mode air door is 1-5.

[0038] 4. Take the range limit values ​​of all control variables, ensure that other control variables remain unchanged, change the value of each control variable one by one, and then record all the results, check the influence of each control variable on the collected value of each sensor in turn, and confirm the control variable with the greatest influencing factor as the main control variable. The calculation formula of the influencing factor is the collected value collected by each sensor minus the corresponding offset, and then multiply it by the weights and add them up. The larger the calculated value, the greater the influencing factor, which means that the control variable is more important to the result.

[0039] 5. Fit the control variables according to the calculation results, calculate the correlation between each sensor value and the control variables, and derive the preliminary correlation formula between the control variables.

[0040] 6. Integrate the N screened control variables to create N*N tables, then calculate the corresponding estimated values ​​according to the correlation formula, and then calibrate the control variables in the controller according to the control variables in the table, and then record the relevant test results to evaluate the deviation and correlation between the actual collected values ​​and the estimated values.

[0041] 7. Organize and analyze the final test results, fit the final Map table, use cubic spline interpolation to smooth the surface, and then perform N-dimensional interpolation calculations according to the dimensions of the control table, and then perform inverse operations. According to the calculation results, reversely solve the control variables, decouple each control variable, and obtain the relationship between the results and the control variables. Change the Map to a control algorithm and integrate it into the controller. When using it, reversely solve the control value according to the set value, and then calculate the deviation in real time according to the feedback value, and correct and filter the control variable.

[0042] 8. Further test the air conditioning controller to test its stability and reliability under other working conditions. If a large deviation occurs, repeat steps 3-7 above for this working condition and then fit it into the Map table.

[0043] The significant advantages of the present invention are as follows:

[0044] 1. Adding multiple sensors to collect the temperature inside the cockpit can accurately restore the environment inside the cockpit and obtain the temperature that the driver intuitively feels, not just the temperature of the air outlet, which can more effectively ensure the driver's comfort.

[0045] 2. Based on the analysis of data from multiple sensors, it can restore external working conditions, such as hot, cold, humid and other weather conditions. According to different working conditions, the damper angle, wind speed, compressor speed, etc. are adjusted to improve comfort.

[0046] 3. Use the analysis system to automatically analyze the data, reduce manual workload, and improve the accuracy of the analysis results. Fit the sensor data according to the analysis results and judge the accuracy of the fitting, so as to obtain more data while using fewer sensors.

[0047] 4. Use the interpolation algorithm to fit the analysis results and form multiple maps for calculation. The interpolation results are smoother and will not have sudden changes. It can adapt to more working conditions and improve the stability and reliability of the algorithm.

[0048] Specifically analyzing the above advantage 4, the fitting result is a multidimensional curve, and the dimension is related to the number of variables. In general programs, three-dimensional tables are used for calibration at most, so multiple tables need to be used for fitting, such as splitting a four-dimensional table into multiple three-dimensional tables for fitting. For example, the original function is a multidimensional table of y=k*x+b, and each variable is a three-dimensional table. In this way, higher-dimensional data can be synthesized to reduce the complexity of calculation and programming. The calculated multiple Maps are discontinuous, and intermediate data will be encountered during actual use. In this case, an interpolation algorithm needs to be used to calculate the intermediate values ​​of the Map. A suitable interpolation algorithm will ensure the smoothness of the curve and avoid sudden changes in the control variables, which will lead to sudden changes in the test results.

[0049] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Any simple modification and equivalent changes made to the above embodiments based on the technical essence of the present invention shall fall within the protection scope of the present invention.

Claims

1. A calibration method for a calibration system of a commercial vehicle air conditioning system based on a multi-sensor multi-actuator, characterized in that: The calibration system comprises: It is mainly composed of multiple temperature sensors arranged inside the cockpit and on the vehicle body, which are used to collect temperature data from multiple air outlets in the cockpit, the driver / co-pilot side and the entire vehicle; The data acquisition and calibration system includes a temperature sensor acquisition tool and a calibration system. The temperature sensor acquisition tool is connected to the calibration sensor system and the air-conditioning controller, and the resistance signal of each temperature sensor is converted into a temperature signal after processing and sent to the air-conditioning controller. The calibration system is connected to the air-conditioning controller, modifies the internal data thereof and allows the air-conditioning controller to upload the collected data in real time; and a data analysis system, including a MATLAB data analysis toolbox associated with a data acquisition and calibration system, for integrating, analyzing, automatically fitting, and optimizing the acquired data to find the optimal control point; The calibration method comprises the following steps: 1) Screening control variables: First, find all the control variables of the commercial vehicle air conditioning system, then list the range of the control variables and find the limit value, modify each variable to the limit value, test it, and then analyze its impact on the test results, and find the N control variables with the largest impact; 2) Test the control variables in sections: Plot the N control variables into N*N tables, where only one row in each table changes equally within the range, and the other values ​​remain unchanged. Then modify the control variables according to the table, and then record the test data and results for each time; 3) Statistical analysis of test results: The test results are unified and integrated, and multiple groups of maps are calculated using an interpolation algorithm. Interpolation is then performed again to calculate multiple points and integrate them into the control algorithm. 4) Optimize test: optimize and delete the test steps according to the analysis results, remove redundant test items, and analyze the matching relationship between working conditions and data; Specifically, the step 3) is to organize and analyze the final test results, fit the final Map table, use cubic spline interpolation to smooth the surface, and then perform N-dimensional interpolation calculation according to the dimension of the control table, and then perform inverse operation, reversely solve the control variables according to the calculation results, decouple each control variable, and obtain the relationship between the result and the control variable; convert the Map into a control algorithm and integrate it into the controller; when in use, reversely solve the control value according to the set value, and then calculate the deviation in real time according to the feedback value, and correct and filter the control variable.

2. The calibration method of the calibration system based on the multi-sensor multi-actuator commercial vehicle air conditioning system according to claim 1, characterized in that: The control variables and their ranges in step 1) include a PWM range of 0 to 100 for the blower, a control range of 0 to 1 for the compressor, a control range of 0 to 1 for the heating and cooling air doors, a control range of 0 to 100 for the internal and external circulation air doors, and a control range of 1 to 5 for the mode air doors.

3. The calibration method of the calibration system based on the multi-sensor multi-actuator commercial vehicle air conditioning system according to claim 1, characterized in that: The test process in step 1) includes: using the MATLAB data analysis toolbox to import the collected data, and transforming the data according to the file format, interpolating according to time, and unifying the time coordinate axis; then calculating the impact amplitude according to the formula, and using the Curve toolbox to automatically fit the curve, analyzing the relationship between the control variables, screening outliers, and fitting to a new formula, and using the optimal control algorithm to find the optimal control point.

4. The calibration method of the calibration system based on the multi-sensor multi-actuator commercial vehicle air conditioning system according to claim 3 is characterized by: The formula for calculating the impact amplitude is to subtract the corresponding offset from the collected value collected by each sensor, and then multiply it by each weight and add them up; the larger the value calculated by this formula, the greater the impact factor, and the more important the control variable is to the result.

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