Vehicle-mounted air conditioner control system based on PSO optimization algorithm of novel air conditioner dummy

Abstract

The invention relates to the technical field of vehicle-mounted air conditioner control, in particular to a vehicle-mounted air conditioner control system based on a PSO optimization algorithm of a novel air conditioner dummy. Comprising an air-conditioning dummy system and an air-conditioning system. The air conditioner dummy system comprises an environment data acquisition module, a main control module and a voice module. The environment data acquisition module is used for acquiring the temperature of each part in real time through an arranged temperature sensor; and the main control module is used for controlling the voice module according to the temperature information acquired by the environment data acquisition module. According to the vehicle-mounted air conditioner control system based on the PSO optimization algorithm of the novel air conditioner dummy, the cold and hot feelings of passengers are represented through the more visual dummy body surface temperature, and the human body surface temperature of a real person is in the state that the human body and the surrounding heat environment reach heat balance; however, the air-conditioning dummy lacks a temperature adjusting process owned by a human body, the temperature collected by the sensor is corrected by using a quadratic function, and the real temperature closer to the passenger is obtained.

Description

Technical Field

[0001] The invention relates to the technical field of vehicle air-conditioning control, and in particular to a vehicle air-conditioning control system based on a PSO optimization algorithm of a novel air-conditioning dummy. Background Art

[0002] As air conditioning systems develop towards comfort and intelligence, achieving dual optimization of human thermal comfort and equipment energy-saving efficiency has become the main goal in the field of thermal environment management. Under this trend, air conditioning dummies, as a key tool for evaluating thermal comfort, play a vital role;

[0003] At present, most air-conditioning dummies directly use formulas to calculate the comfort in a certain scenario, such as PMV-PDD, etc. However, there are the following disadvantages in using formulas to evaluate comfort in actual applications: individual differences are difficult to reflect. For example, the elderly and young people have different sensitivities to temperature. It is difficult for the formula to take into account such individual physiological and psychological differences, which may cause the evaluation results to be inconsistent with the actual feelings. Environmental factors are complex, and comfort is affected by the interaction of multiple environmental factors. Although some formulas consider factors such as temperature, humidity, and wind speed, factors such as radiant heat, air quality, and noise are difficult to accurately incorporate into the formula. The adaptability to dynamic changes is poor, and people's comfort will change dynamically over time and will also be affected by the state of activity. After exercise, people will change their requirements for the comfort range of environmental conditions such as temperature and humidity, and it is difficult for existing formulas to accurately evaluate comfort in real time and flexibly based on these dynamic changes. The structure of the dummy is also relatively complex, with many sensors and high cost;

[0004] Since the air-conditioning dummy cannot simulate the heat generated by the human body's metabolic process, it cannot completely simulate the actual temperature state of a real person in the car, resulting in differences in temperature test data. The surface temperature of a real person's body is the state in which the human body reaches thermal equilibrium with the surrounding thermal environment, while the air-conditioning dummy lacks the temperature regulation process that the human body has, resulting in a certain deviation between the collected surface temperature of the air-conditioning dummy and the surface temperature of real people's clothes;

[0005] When the driver is driving, manually operating the air conditioning panel may distract the driver's attention, while it is more convenient for users to use the in-vehicle voice system. The system can quickly recognize the command and set the air conditioning temperature to a precise degree. However, for passengers, the sudden drop in air conditioning temperature does not make passengers feel very comfortable. Because passengers do not understand their own temperature and the air conditioning system, the temperature may drop to the set value, causing the passengers to be too cold or too hot. Passengers need to adjust the air conditioning temperature a second time, which not only makes the passengers less comfortable but also increases the energy consumption of the air conditioning.

[0006] To this end, a vehicle air-conditioning control system based on a PSO optimization algorithm of a new air-conditioning dummy is designed to provide another technical solution to the above technical problems. Summary of the invention

[0007] Based on this, it is necessary to provide a vehicle air-conditioning control system based on a PSO optimization algorithm of a new air-conditioning dummy to solve the technical problems raised in the above background technology.

[0008] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0009] A vehicle air-conditioning control system based on a new PSO optimization algorithm for air-conditioning dummy, including an air-conditioning dummy system and an air-conditioning system;

[0010] The air-conditioning dummy system includes an environmental data acquisition module, a main control module and a voice module;

[0011] The environmental data acquisition module is used to collect the temperature of each part in real time through the arranged temperature sensors;

[0012] The main control module is used to control the voice module according to the temperature information collected by the environmental data collection module;

[0013] The voice module is used to perform voice broadcasting according to the model of the main control module;

[0014] The air conditioning system is used to adjust the air conditioning according to the control of the air conditioning dummy system to control the opening and closing size of the air outlet;

[0015] The air conditioning system includes an air conditioning control module, which is used to control the passenger's own cold and hot sensations through a voice recognition module designed to correspond to the voice module.

[0016] As a preferred implementation of the vehicle air-conditioning control system based on a PSO optimization algorithm for a new type of air-conditioning dummy provided by the present invention, the environmental data acquisition module is a temperature sensor.

[0017] As a preferred implementation of the vehicle air-conditioning control system based on the PSO optimization algorithm of a new air-conditioning dummy provided by the present invention, the temperature sensors are respectively arranged at 16 parts corresponding to the human body, namely the head, chest, back, pelvis, left / right upper arm, left / right forearm, left / right hand, left / right thigh, left / right calf, and left / right foot.

[0018] As a preferred implementation of the vehicle air-conditioning control system based on the PSO optimization algorithm of a new air-conditioning dummy provided by the present invention, the voice module is designed with 32 voice signal outputs, which are used to sense overcooling or overheating of 16 parts of the head, chest, back, pelvis, left / right upper arm, left / right forearm, left / right hand, left / right thigh, left / right calf, and left / right foot.

[0019] As a preferred implementation of the vehicle air-conditioning control system based on a PSO optimization algorithm for a new type of air-conditioning dummy provided by the present invention, the main control module includes a data processing module and a control unit module;

[0020] The data processing module is used to correct the temperature collected by the temperature sensor;

[0021] The control unit module is used to determine the temperature of various parts of the human body after receiving the data from the data processing module.

[0022] As a preferred implementation of the vehicle air-conditioning control system based on the PSO optimization algorithm of a new air-conditioning dummy provided by the present invention, if the temperature of each part is within the comfortable temperature, no processing is performed; if the temperature of each part is out of the comfortable temperature and is judged to be overheated, a signal is fed back to the voice system; if it does not reach the comfort range and is judged to be too cold, a signal is fed back to the voice system.

[0023] As a preferred implementation of the vehicle air-conditioning control system based on a PSO optimization algorithm of a new air-conditioning dummy provided by the present invention, it also includes an air-conditioning model for adjusting the air outlet wind speed of the air-conditioning according to the hot and cold states in the real-time voice signal of the occupant.

[0024] As a preferred implementation of the vehicle air-conditioning control system based on a PSO optimization algorithm for a new type of air-conditioning dummy provided by the present invention, the air-conditioning model is constructed in the following steps:

[0025] Place the particle air conditioner outlet;

[0026] The solution space is defined as the air conditioning control system;

[0027] The objective function value is defined as the passenger's comfort temperature, specifically the fitness value;

[0028] A solution in space is defined as the opening of each air-conditioning outlet, specifically the particle position;

[0029] The global optimal solution is defined as the outlet opening that is most frequently used during the iteration process.

[0030] As a preferred implementation of the vehicle air conditioning control system based on the PSO optimization algorithm of a new air conditioning dummy provided by the present invention, the fitness function is defined based on the difference between the passenger body temperature and the comfortable body temperature, and the expression is as follows:

[0031]

[0032] The passenger's body temperature is T i , the target comfortable body temperature is T target ;

[0033] If f>0, the overall passenger temperature is higher than the target temperature, and the temperature needs to be lowered; if f<0, the overall passenger temperature is lower than the target temperature, and the temperature needs to be raised;

[0034] For the six air outlets of the vehicle air conditioner, 0 represents closed and 1 represents open for encoding, and the wind speed is discretized into multiple levels to complete the vector representation of the six air outlets of the vehicle air conditioner;

[0035] For each particle’s position vector, the open / closed state and wind speed level are randomly initialized;

[0036] Iteratively update the particles, the expression is as follows:

[0037] v ji (t+1)=w*v ji (t)+c 1 *r 1 *(p ji -x ji (t))+c 2 *r 2 *(g i -x ji (t))

[0038] Where w is the inertia weight, c 1 and c 2 is the learning factor, r 1 and r 2 is a random number between [0,1], p ji is the i-th dimension of the best position experienced by particle j, g i is the i-th dimension of the best position experienced by the group, x ji (t) is the i-th dimension of the position of particle j at the t-th iteration;

[0039] Position vector x j The i-th dimension of is updated at the t+1th iteration, and the expression is as follows:

[0040] x ji (t+1)=x ji (t)+v ji (t+1)

[0041] The fitness value is calculated based on the structure of the position update.

[0042] It can be seen without a doubt that the above-mentioned technical solution of the present application can definitely solve the technical problem to be solved by the present application.

[0043] At the same time, through the above technical solutions, the present invention has at least the following beneficial effects:

[0044] 1. The vehicle air-conditioning control system based on a PSO optimization algorithm of a new air-conditioning dummy provided by the present invention does not use a complex comfort formula to evaluate comfort, but uses a more intuitive dummy surface temperature to represent the occupant's feeling of cold or hot. The surface temperature of a real human body is a state in which the human body and the surrounding thermal environment reach thermal equilibrium, while the air-conditioning dummy lacks the temperature regulation process possessed by the human body, resulting in a certain deviation between the collected surface temperature of the air-conditioning dummy and the surface temperature of real clothes. By using a quadratic function to correct the temperature collected by the sensor, a temperature closer to the real temperature of the occupant is obtained.

[0045] 2. Compared with the traditional comfort dummy model, the sensor setting of the dummy is relatively simple. The dummy environment acquisition module is only equipped with a temperature sensor. Compared with the traditional air-conditioning dummy (generally equipped with multiple sensors such as temperature, humidity, wind speed, thermal radiation, etc.), the dummy structure complexity and cost are reduced, while the data processing volume is reduced and the system operation efficiency is improved. The air-conditioning dummy can collect and feedback the temperature of various parts in real time through the voice system, and the air-conditioning system can respond and adjust quickly. For example, in the cooling mode, the specific air outlet is fully opened or half opened, which can quickly reduce the temperature in the car and improve the comfort of the passengers.

[0046] 3. The present invention divides the dummy into blocks and obtains different correction formulas for each part according to different temperatures. According to the different hot and cold sensations of each part of the passenger (such as different hot and cold sensations of the head and feet at the same temperature), an optimal temperature range is set for each part of the dummy. When it is not within the set range, the voice interaction system of the dummy will receive a signal saying whether it is cold or hot at this moment, and the air-conditioning system will adjust the opening and closing size of the air outlet after receiving the voice.

[0047] 4. The air-conditioning voice recognition module of the present invention controls the opening and closing size of the air outlet according to the passengers' feeling of cold and heat. Compared with the traditional method of adjusting the temperature only according to the passengers' setting, it can more effectively improve the comfort of specific parts. It has three modes: cooling, comfort and heating. In each mode, the working state of each air outlet is reasonable, and four wind speed modes of fully closed, slightly open, half open and fully open are set according to different needs, which can accurately meet the comfort needs of passengers in different scenarios.

[0048] 6. The present invention adopts the PSO optimization algorithm to train the air-conditioning system. When the vehicle driving environment changes rapidly, it can respond to changes more quickly and adjust to the optimal air outlet size in time to ensure that the air-conditioning control strategy always remains optimal, thereby ensuring driver comfort and improving energy utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0050] Figure 1 A schematic diagram of the division of sensors at various parts of a dummy according to the present invention;

[0051] Figure 2 It is a schematic diagram of a dummy control system of the present invention;

[0052] Figure 3 It is a schematic diagram of the arrangement structure of each air outlet of the present invention;

[0053] Figure 4 Schematic diagram of the air conditioning control system of the present invention. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. 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.

[0055] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings.

[0056] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features and technical solutions in the embodiments may be combined with each other.

[0057] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0058] Reference Figure 1-Figure 4 , a vehicle air-conditioning control system based on a PSO optimization algorithm of a new air-conditioning dummy.

[0059] In order to keep up with the development trend of air conditioning becoming more and more comfortable and intelligent, the PSO optimization algorithm is used to train the opening and closing and size of the air outlet of the vehicle air conditioner, so that the driver can have better comfort. In actual processes, the driver of the passenger often controls the air conditioning temperature and the size of the air outlet, which often makes himself too cold or too hot, so the air conditioning data of the actual vehicle cannot reflect the real-time comfort of the passengers. The present invention uses the simple dummy system and the control method of the corresponding air conditioning system, and uses the characteristics of the air conditioning dummy's real-time temperature response to obtain the data of the air conditioning outlet to train the air conditioning system, and obtains the optimized air conditioning system model, which is then burned into the actual vehicle air conditioning system.

[0060] 1. Air conditioning dummy system

[0061] The air-conditioning dummy system includes an environmental data acquisition module, a main control module and a voice module;

[0062] The environmental data acquisition module is a temperature sensor, which is set at least in 16 parts of the human body - head, chest, back, pelvis, left / right upper arm, left / right lower arm, left / right right hand, left / right thigh, left / right calf, left / right foot, so that the temperature of each part can be collected in real time through the arranged temperature sensors. For details, please refer to Figure 1 , Figure 1 The numbers in the figure are temperature sensors, and the corresponding positions of the numbers are as follows:

[0063] 1-head, 2-chest, 3-right upper arm, 4-left upper arm, 5-right forearm, 6-left forearm, 7-right hand, 8-left hand, 9-pelvis, 10-right thigh, 11-left thigh, 12-right calf, 13-left calf, 14-right foot, 15-left foot, 16-back.

[0064] The main control module is used to control the voice module according to the temperature information collected by the environmental data collection module;

[0065] The main control module includes a data processing module and a control unit module;

[0066] The data processing module is used to correct the temperature collected by the temperature sensor;

[0067] The surface temperature of a real human body is the state in which the human body reaches thermal equilibrium with the surrounding thermal environment, but the air-conditioning dummy lacks the temperature regulation process possessed by the human body, resulting in a certain deviation between the collected surface temperature of the air-conditioning dummy and the surface temperature of real clothes. Correction experiments have shown that after the surface temperature of the air-conditioning dummy is corrected using a quadratic function, the error generated by the correction calculation is about 1% to 3%. Use a quadratic function for fitting: use the temperature of the air-conditioning dummy as the horizontal coordinate (x-axis), and the surface temperature of real clothes as the vertical coordinate (y-axis), and fit the functional relationship between the surface temperature of real clothes at different positions of the human body and the temperature of the air-conditioning dummy: y=f(x). The specific steps of the correction function are as follows: take the temperature collected by the temperature sensor as input, and correct it with a quadratic function to obtain a temperature closer to the actual human body. Assume that the correction function of a certain part is such as: y=0.0115x 2 +1.6447x+7.07, where x is the temperature collected by the temperature sensor and y is the corrected temperature.

[0068] The control unit module is used to judge the temperature of various parts of the human body after receiving the data from the data processing module. If the temperature of each part is within the comfortable temperature, no processing is performed. If the temperature of each part is out of the comfortable temperature and is judged to be overheated, the signal is fed back to the voice system. If it does not reach the comfort range and is judged to be too cold, the signal is fed back to the voice system.

[0069] The voice module is used to make voice broadcasts according to the model of the main control module, and the output text is: I feel hot or cold in a certain part of the body. At the same time, it can also be divided into a little hot or very hot according to the regional temperature of the divided body parts and the degree of degree.

[0070] In order to correspond to the sensor module of the environment acquisition module, the voice module is also designed to output 32 voice signals, which can sense at least 16 parts of the body, including the head, chest, back, pelvis, left / right upper arm, left / right forearm, left / right hand, left / right thigh, left / right calf, and left / right foot, if they are too cold or too hot.

[0071] The comfortable temperature range set for 16 parts of the dummy is 22-26℃ (the comfortable body temperature felt by normal people). When the temperature of all parts of the dummy is within this range, the dummy voice module outputs: This temperature feels very comfortable. The air-conditioning voice recognition module recognizes the dummy's comfortable signal and switches the mode to comfort mode.

[0072] When 0-8 parts of the dummy exceed the comfortable temperature range, the dummy main control module sends a signal to control the dummy voice module to output: I feel a little hot, the air conditioner is set to cooling mode (the air outlet is adjusted to half-open mode)

[0073] When 8-16 parts of the dummy exceed the comfortable temperature, the dummy voice module outputs: I feel very hot, and the air conditioner is set to cooling mode (the air outlet is fully open).

[0074] The advantage of using an air conditioning dummy for testing is that it can reflect the temperature of the occupants in real time, making the air conditioning system respond more quickly. The air conditioning dummy's voice system can respond immediately and the air conditioning system can adjust.

[0075] 2. Air conditioning system

[0076] The air conditioning system is used to adjust the air conditioning according to the control of the air conditioning dummy system to control the opening and closing size of the air outlet;

[0077] It also includes an air conditioning control module, which is used to perform the passenger's own hot and cold feelings through a voice recognition module designed to correspond to the voice module of the voice recognition module and the voice module of the dummy system, so that the air conditioning controls the opening and closing size of the air outlet to greatly improve the comfort of a certain part of the passenger, avoiding the traditional voice recognition to obtain information for the passenger to tell the passenger how many degrees to set the temperature in the car, thereby improving the passenger's comfort experience.

[0078] refer to Figure 3 , the working mode is as follows:

[0079] 1. Cooling mode

[0080] Air outlet working status:

[0081] Figure 3 In the figure, 1-left air outlet, 3-middle air outlet, and 6-right air outlet are all open. These three main front air outlets can quickly blow a large amount of cold air into the car. The cold air circulates in the car, which can quickly reduce the temperature in the car and bring a cool feeling to the people in the car. 2-Front windshield air outlet is closed. Because the front windshield does not need special treatment during the cooling process, closing this air outlet can allow more cold air to be used to reduce the temperature in the car. 4-Front passenger foot air outlet: closed. In the rapid cooling stage, concentrating the cold air on the upper part of the car can reduce the temperature more efficiently, and the sensitivity of the feet to temperature is relatively low in the early stage of cooling. 5-Side defogger air outlet: closed. If the humidity in the car is normal and the side windows are foggy, closing this air outlet can use more cold air for overall cooling.

[0082] 2. Comfort Mode

[0083] Air outlet working status:

[0084] Figure 31-Left air outlet, 3-Middle air outlet, 6-Right air outlet: open, adjust the wind speed to medium. Provide a continuous and comfortable air environment for the people in the car and keep the temperature in the car stable. 2-Front windshield air outlet: closed (if the front windshield is not fogged). If the risk of fogging is detected, it will automatically open at a low wind speed and appropriate temperature to prevent fog from affecting the vision. 4-Front passenger foot air outlet: open, the wind speed is low, and the temperature is consistent with other air outlets. Provide a comfortable temperature environment for the feet of the front passengers and promote good air circulation in the car. 5-Side defogger air outlet: closed (if there is no fog on the side window). If there are signs of fogging on the side window, it will automatically open at a low wind speed and appropriate temperature to ensure that the side window is clear.

[0085] 3. Heating mode

[0086] Air outlet working status:

[0087] Figure 3 4-Front passenger foot outlet: open, wind speed adjusted to high. Focus on providing warm air to the front passenger's feet, especially in cold weather, which can quickly warm up the feet and improve the comfort of the whole body. 1-Left air outlet, 3-Middle air outlet, 6-Right air outlet: open, wind speed adjusted to low. Maintain moderate air circulation and temperature in the upper part of the car to avoid excessively high or low temperature in the upper part of the car due to focusing only on keeping the feet warm.

[0088] Air conditioner outlet wind speed setting:

[0089] Fully closed mode: At this time, the blades of the air outlet are tightly closed, and almost no air flows out. This mode is suitable for situations where the air outlet is not needed, such as when passengers feel uncomfortable with a certain air outlet blowing directly on their body, or when they want to concentrate the air conditioning air to other areas.

[0090] Slightly open mode: adjust the air outlet to a state where you can just feel a small amount of air flowing out. The opening is usually around 10%-30%. In this mode, the air volume delivered is small. It is more suitable for situations where strong wind is not needed but a little air flow is desired. For example, passengers are sensitive to wind and only want a slight air circulation to maintain comfort.

[0091] Half-open mode: The air outlet is opened at about 40%-60%, which can deliver a moderate amount of air. While ensuring a certain ventilation effect, the wind will not be too strong. For example, it can be used when the temperature in the car is relatively comfortable and only proper air circulation is needed to maintain this state.

[0092] Fully open mode: The air outlet is fully open, the blades are at the maximum opening angle, and the maximum air volume can be delivered. When you need to quickly adjust the temperature in the car, such as quickly cooling down in summer or quickly heating up in winter, this mode allows the air conditioning air to circulate in the car to the greatest extent.

[0093] Embodiment 2

[0094] refer to Figure 4 Based on the information provided in the above embodiment 1, an application is provided.

[0095] The air conditioning dummy system and air conditioning system are applied to the intelligent control of the real vehicle air conditioning system. The method is as follows:

[0096] Training of the conditioning model

[0097] In order to make passengers more comfortable, the air outlet speed of the air conditioner must be set to suit the passenger's current temperature. In order to make the air outlet speed of the air conditioner closer to the passenger's real-time temperature, the present invention burns the trained air conditioning model into the actual vehicle air conditioning system. The following are the steps for training the air conditioning system model:

[0098] First, the data for training the model needs to be extracted. The air outlet data of 2,000 sets of air-conditioning dummies when they are adjusted from overheated and overcooled states to comfortable states need to be exported as the data for training the air-conditioning model.

[0099] Next, we design the PSO algorithm for opening and closing the air outlet. The logic of the PSO (Part icl eSwarm Optimization) algorithm is as follows: each particle searches for the optimal solution in the search space individually, and records it as the current individual extreme value, and shares the individual extreme value with other particles in the entire particle swarm. The optimal individual extreme value is found as the current global optimal solution of the entire particle swarm. All particles in the particle swarm adjust their speed and position according to the current individual extreme value they find and the current global optimal solution shared by the entire particle swarm. Advantages of the PSO algorithm: During the driving process of the vehicle, the changes in the in-vehicle environment may be very rapid. The vehicle air conditioning system trained by the PSO algorithm can respond to these changes faster. After receiving the driver's voice signal, it can be adjusted to the optimal air outlet size in time, and the driver's voice signal can be detected in real time to adjust the subsequent air outlet opening to ensure the driver's comfort during driving.

[0100] The core components of the PSO algorithm are: particles, solution space, objective function value (fitness value), a solution in the space (particle position), and the global optimal solution.

[0101] The present invention defines these parts as follows:

[0102] Particles: Each air conditioner outlet

[0103] Solution space: the entire air conditioning system

[0104] Objective function value (fitness value): passenger comfort temperature

[0105] A solution in space (particle position): the opening of each air-conditioning outlet

[0106] Global optimal solution: the outlet opening that is most frequently used during the iteration process

[0107] Air conditioning system problem definition and coding

[0108] Define the fitness function:

[0109] First, a fitness function is defined to evaluate the quality of each particle (representing an air conditioning outlet control strategy). The fitness function is defined based on the difference between the passenger's body temperature and the comfortable body temperature. The passenger's body temperature is T i , the target comfortable body temperature is T target , define the fitness function:

[0110]

[0111] If f>0, it means that the overall body temperature of the passengers is higher than the target temperature and needs to be further cooled; if f<0, it means that the overall body temperature of the passengers is lower than the target temperature and needs to be heated up next.

[0112] Particle encoding:

[0113] For the six air outlets of the vehicle air conditioner, each outlet has different states, including open and closed states (0 for closed and 1 for open). The wind speed is discretized into several levels, 1 for low wind speed, 2 for medium wind speed, and 3 for high wind speed. A particle can be represented by a vector of length 12. For example, the vector [1, 2, 0, 1, 1, 3, 1, 0, 0, 1, 1, 2], the first 6 elements represent the open and closed states of the air outlet, and the last 6 elements represent the corresponding wind speed levels.

[0114] Initialize particle swarm

[0115] Since there are six air outlets in total, the air outlet states are open and closed, and one air outlet has three wind speeds, the size of the particle group is defined as 2 6 ×3 6 =46656 different air conditioning outlet control strategies.

[0116] Initialize particle positions and velocities:

[0117] For each particle's position vector (i.e., outlet control strategy vector), the open / close state (0 or 1) and wind speed level (0-3) are randomly initialized. For the velocity vector, since each dimension represents the change trend of the outlet state or wind speed, each dimension of the velocity vector can be initialized to a random number between [-1-1]. For example, for a 12-dimensional velocity vector, the value of each dimension may be a random number such as -0.11, +0.2, etc.

[0118] Iterative update process

[0119] Speed ​​update formula:

[0120] For particle j (j = 1, 2, 3, ..., m), it is represented by v ji (t+1), its velocity vector v j The i-th dimension (i=1,2,3,……,12) of

[0121] The update formula of generation time can be:

[0122] v ji (t+1)=w*v ji (t)+c 1 *r 1 *(p ji -x ji (t))+c 2 *r 2 *(g i -x ji (t))

[0123] Where, w is the inertia weight (eg), c 1 and c 2 is the learning factor, r 1 and r 2 is a random number between [0,1], p ji is the i-th dimension of the best position experienced by particle j, g i is the i-th dimension of the best position experienced by the group, x ji (t) is the i-th dimension of the position of particle j at the t-th iteration.

[0124] Position vector x j The i-th dimension of is updated at the t+1th iteration as:

[0125] x ji (t+1)=x ji (t)+v ji (t+1)

[0126] For the result after the position vector is updated, the dimension of the open and closed state needs to be guaranteed to be 0 or 1, which can be achieved by rounding; the dimension of the wind speed level needs to be guaranteed to be within the defined wind speed level range. If it exceeds the range, boundary processing is performed. During the entire operation process, each time the position of the particle is updated, its corresponding fitness value needs to be calculated. Next, the fitness value of the particle after this update is compared with the fitness value corresponding to its individual optimal position. If it is found that the fitness value of this particle after the update is better, then the current position of this particle is used to replace its original individual optimal position to complete the update operation of the individual optimal position. After the individual optimal positions of all particles are updated, the fitness value of the individual optimal position of each particle should be further compared with the fitness value of the group optimal position. Once it is found that the fitness value of a certain individual optimal position is better than the fitness value of the group optimal position, then this better individual optimal position is used to update the group optimal position in time. After the end, the trained algorithm is burned into the actual vehicle system, and the driver is kept at the optimal body temperature according to the control strategy of this air-conditioning system.

[0127] The effect achieved is: when the driver feels overheated or overcooled during driving, he no longer needs to manually adjust the temperature and wind speed of the air conditioner. He only needs to tell the hot or cold feeling of a certain part of his body, and the air conditioning system can intelligently adjust the opening and feeling of the air outlet, which can prevent the driver from being distracted during driving. The trained air conditioning system makes the air conditioning control faster and closer to the comfort of the driver at this time, greatly improving the comfort of the driver. The method proposed by the present invention is not only aimed at the setting of this kind of air outlet, but also not limited to the position of the dummy.

[0128] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the present invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A vehicle air conditioning control system based on a new PSO optimization algorithm for air conditioning dummy, characterized in that: Including air conditioning dummy system and air conditioning system; The air-conditioning dummy system includes an environmental data acquisition module, a main control module and a voice module; The environmental data acquisition module is used to collect the temperature of each part in real time through the arranged temperature sensors; The main control module is used to control the voice module according to the temperature information collected by the environmental data collection module; The voice module is used to perform voice broadcasting according to the model of the main control module; The air conditioning system is used to adjust the air conditioning according to the control of the air conditioning dummy system to control the opening and closing size of the air outlet; The air conditioning system includes an air conditioning control module, which is used to control the passenger's own cold and hot sensations through a voice recognition module designed to correspond to the voice module.

2. The vehicle air conditioning control system based on a PSO optimization algorithm of a new air conditioning dummy according to claim 1 is characterized in that: The environmental data acquisition module is a temperature sensor.

3. The vehicle air conditioning control system based on a PSO optimization algorithm of a new air conditioning dummy according to claim 2 is characterized in that: The temperature sensors are respectively arranged at 16 corresponding parts of the human body, namely the head, chest, back, pelvis, left / right upper arm, left / right forearm, left / right hand, left / right thigh, left / right calf, and left / right foot.

4. The vehicle air conditioning control system based on a PSO optimization algorithm of a new air conditioning dummy according to claim 3 is characterized in that: The voice module is designed with 32 voice signal outputs, which are used to correspond to the sensor module of the environment acquisition module, and respectively sense that 16 parts of the body, including the head, chest, back, pelvis, left / right upper arm, left / right forearm, left / right hand, left / right thigh, left / right calf, and left / right foot, are too cold or too hot.

5. The vehicle air conditioning control system based on a PSO optimization algorithm of a new air conditioning dummy according to claim 4 is characterized in that: The main control module includes a data processing module and a control unit module; The data processing module is used to correct the temperature collected by the temperature sensor; The control unit module is used to determine the temperature of various parts of the human body after receiving the data from the data processing module.

6. The vehicle air conditioning control system based on a PSO optimization algorithm of a new air conditioning dummy according to claim 5 is characterized in that: If the temperature of each part is within the comfortable temperature, no processing will be done. If the temperature of each part is out of the comfortable temperature and is judged to be overheated, the signal will be fed back to the voice system. If it does not reach the comfortable range, it will be judged to be too cold, and the signal will be fed back to the voice system.

7. The vehicle air conditioning control system based on a PSO optimization algorithm of a new air conditioning dummy according to any one of claims 1 to 6, characterized in that: It also includes an air-conditioning model, which is used to adjust the air speed of the air-conditioning outlet according to the hot and cold status in the real-time voice signal of the occupants.

8. The vehicle air conditioning control system based on a PSO optimization algorithm of a new air conditioning dummy according to claim 7 is characterized in that: The air conditioning model is constructed in the following steps: Place the particle air conditioner outlet; The solution space is defined as the air conditioning control system; The objective function value is defined as the passenger's comfort temperature, specifically the fitness value; A solution in space is defined as the opening of each air-conditioning outlet, specifically the particle position; The global optimal solution is defined as the outlet opening that is most frequently used during the iteration process.

9. The vehicle air conditioning control system based on a PSO optimization algorithm of a new air conditioning dummy according to claim 8 is characterized in that: The fitness function is defined based on the difference between the passenger's body temperature and the comfortable body temperature. The expression is as follows: The passenger's body temperature is T i , the target comfortable body temperature is T target ; If f>0, the overall passenger temperature is higher than the target temperature, and the temperature needs to be lowered; if f<0, the overall passenger temperature is lower than the target temperature, and the temperature needs to be raised; For the six air outlets of the vehicle air conditioner, 0 represents closed and 1 represents open for encoding, and the wind speed is discretized into multiple levels to complete the vector representation of the six air outlets of the vehicle air conditioner; For each particle’s position vector, the open / closed state and wind speed level are randomly initialized; Iteratively update the particles, the expression is as follows: v ji (t+1)=w*v ji (t)+c1*r1*(p ji -x ji (t))+c2*r2*(g i -x ji (t)) Among them, w is the inertia weight, c1 and c2 are learning factors, r1 and r2 are random numbers between [0,1], and p ji is the i-th dimension of the best position experienced by particle j, g i is the i-th dimension of the best position experienced by the group, x ji (t) is the i-th dimension of the position of particle j at the t-th iteration; Position vector x j The i-th dimension of is updated at the t+1th iteration, and the expression is as follows: x ji (t+1)=x ji (t)+v ji (t+1) The fitness value is calculated based on the structure of the position update.

Images